Methods and apparatus for determining characteristics of particles

ABSTRACT

An instrument for measuring the size distribution of a particle sample by counting and classifying particles into selected size ranges. The particle concentration is reduced to the level where the probability of measuring scattering from multiple particles at one time is reduced to an acceptable level. A light beam is focused or collimated through a sample cell, through which the particles flow. As each particle passes through the beam, it scatters, absorbs, and transmits different amounts of the light, depending upon the particle size. So both the decrease in the beam intensity, due to light removal by the particle, and increase of light, scattered by the particle, may be used to determine the particle size, to classify the particle and count it in a certain size range. If all of the particles pass through a single beam, then many small particles must be counted for each large one because typical distributions are uniform on a particle volume basis, and the number distribution is related to the volume distribution by the particle diameter cubed.

CROSS-REFERENCE TO PRIOR APPLICATIONS

This is a continuation of U.S. patent application Ser. No. 11/538,669,filed Oct. 4, 2006, which is a continuation-in-part of U.S. patentapplication Ser. No. 10/598,443, filed Aug. 30, 2006, which is a U.S.national phase of PCT/US2005/07308, which claims the priority of U.S.provisional application Ser. No. 60/550,591, filed Mar. 6, 2004.Priority is also claimed from U.S. provisional application Ser. No.60/723,639, filed Oct. 5, 2005.

BACKGROUND OF THE INVENTION

This invention relates to systems and methods for analyzing particles ina sample using laser light diffraction. More particularly, the presentinvention relates to systems and methods that analyze laser lightdiffraction patterns to determine the size of particles in a sample.

SUMMARY OF THE INVENTION

The present invention comprises apparatus for optimizing path length ofa light beam through a particle dispersion to improve accuracy ofmeasurement of light scattered from particles, comprising: a) an opticalsystem for illuminating a particle dispersion, b) a detection systemcomprising at least one detector for quantifying light scattered by atleast one of said particles, c) a sample cell, comprising two opticalwindows, which confine said particle dispersion and pass light, from alight source, through said particle dispersion to produce lightscattered by said particle dispersion, and d) means for adjusting aseparation between said optical windows to change a path length oflight, from said light source, through said sample cell.

The invention also comprises a method for determining an optimum pathlength of a light beam passing through a particle dispersion, so as toreduce inaccuracies in particle analysis caused by multiple scatteringof light from particles, the method comprising the steps of: a)determining a specified value of a path length which produces excessivemultiple scattering, b) adjusting said path length to a specified value,c) measuring first scattered light values at said specified value ofpath length, d) reducing said path length to a second value, e)measuring second scattered light values at said second value of saidpath length, f) determining a difference between said second scatteredlight values and said first scattered light values, g) if saiddifference is greater than a specified limit, repeating steps (b)through (f), while setting said specified value of path length, in step(b), to said second value of said path length, h) if said difference isless than a specified limit, using said second scattered light values todetermine particle characteristics.

The invention also comprises a method for determining an optimum pathlength of a light beam passing through a particle dispersion, so as toreduce inaccuracies in particle analysis caused by scatteringmeasurement errors, the method comprising the steps of: a) adjusting apath length to a specified value, b) measuring scattered light values atsaid specified value of said path length, c) calculating an optimumvalue of path length based upon said specified value of said path lengthand said scattered light values, d) adjusting said path length to saidoptimum value of path length, e) measuring scattered light values atsaid optimum value of path length and using scattered light values todetermine particle characteristics.

The invention also comprises apparatus for measuring scattered lightfrom individual particles which are nearly confined to a plane on asurface or in a thin layer of a dispersant, comprising: a) an opticalsystem for illuminating said particles, b) a detection system comprisingat least one detector for quantifying light scattered from a specificregion on said plane, and c) mechanical means for moving an interactionvolume of said optical system and detection system to various locationson said plane to measure separately light scattered at each location.

The invention also comprises apparatus for removing angular drift in asystem for analyzing particles, comprising: a) an optical system forilluminating a particle dispersion, b) a detection system comprising atleast one detector for quantifying light scattered by at least oneparticle, and c) a sample cell, comprising two optical windows, whereinthe windows confine the particle dispersion and pass light, from a lightsource, through said particle dispersion to produce light scattered bysaid particle dispersion, wherein said optical system and detectionsystem are attached to a first side of said sample cell, and wherein theapparatus includes a retroreflector positioned in a vicinity of a secondside of said sample cell, wherein the retroreflector comprises means forremoving angular drift of a light beam caused by drift in position, ordrift in optical properties, of said optical system, said sample cell,and/or said detection system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 provides a schematic diagram of a scattering plane view of ascattering detection system which detects scattered light from particlesin a small volume, according to the present invention.

FIG. 1A provides a schematic diagram showing an aperture which controlsthe light intensity profile of a light source, according to the presentinvention.

FIG. 2 provides a diagram showing the common volume between the lightsource and the viewing volumes of various detectors according to thepresent invention, the scatter volume common to all detectors beingdetermined by detector 113.

FIG. 2 a provides a variation of FIG. 2, wherein the common scattervolume is determined by detector 111.

FIG. 3 provides a variation of FIG. 1, where lens 303 and lens 304 areon opposite sides of the light beam.

FIG. 4 provides a schematic diagram of a signal conditioning circuitwhich detects the envelope of a signal, as used in the presentinvention.

FIG. 5 provides a schematic diagram of an automated system for providingoptical alignment of the system of FIG. 1.

FIG. 6 provides a variation of FIG. 5, showing the use of an analogmultiplier.

FIG. 6 a provides a graph showing an example of scatter signals from asystem as shown in FIG. 1.

FIG. 7 provides a block diagram of a peak detection system which usesanalog electronic devices to reduce the data rate requirements of theanalog to digital converter, according to the present invention.

FIG. 8 provides a variation of the system shown in FIG. 7.

FIG. 9 provides a schematic diagram of the peak detector circuit used inthe present invention.

FIG. 9 a provides a diagram of a wedge shaped particle dispersion samplecell, which provides a linearly increasing maximum particle size acrossthe cell, according to the present invention.

FIG. 10 provides a surface plot of a particle count distribution versusa scattering signal amplitude and a ratio of two scattering signals,according to the present invention.

FIG. 10 a shows a section of the surface plot of FIG. 10.

FIG. 11 provides a schematic diagram of an optical system which measuresthe amount of scattered light removed from the beam by each of manyparticles at the same time, according to the present invention.

FIG. 12 provides a schematic diagram of an optical system which measuresscattered light from different ranges of scattering angle, from a smallvolume in the particle dispersion sample cell, according to the presentinvention.

FIG. 13 provides a schematic diagram of a particle sample system whichadjusts particle concentration to an optimum value, according to thepresent invention.

FIG. 14 provides a schematic drawing of an optical system which measuresthe light scattered, in multiple ranges of scattering angle, by each ofmany particles at the same time, according to the present invention.

FIG. 15 provides a schematic drawing of an optical system whichseparates particle scatter signals based upon signal frequency andscattering angle, with a periodic mask for providing modulation of thescattering signal for particles passing through the sample cell,according to the present invention.

FIG. 15 a provides a schematic diagram of an optical system whichseparates the amounts of scattered light, removed from the light beam,based upon signal frequency, according to the present invention.

FIG. 16 depicts various masks to be utilized in the optical systems ofFIG. 15 and FIG. 15 a.

FIG. 16 a depicts a mask, to be utilized in FIG. 15 and FIG. 15 a, whichreduces the detection volume and increases the signal frequency forsmaller particles.

FIG. 16 b depicts a variation of FIG. 16 a, where the detection volumeand signal frequency changes continuously across the mask.

FIG. 16 c depicts a scatter detector array which defines particleinteraction volumes of varying size across the array, according to thepresent invention.

FIG. 17 provides graphs showing power spectra of signals measured at twoscattering angles for the apparatus depicted in FIG. 15.

FIG. 18 provides a schematic diagram of an optical system which producesa modulated intensity profile by interference of two light beams,instead of imaging a periodic mask according to the present invention.

FIG. 19 provides a schematic diagram showing the use of detector size todefine the angular range of each detector in FIG. 1.

FIG. 20 provides a diagram showing more detail of the light beam focusand the focus of each detector field of view, using the conceptsdepicted in FIG. 2 and FIG. 2 a.

FIG. 21 provides a diagram of a particle dispersion sample cell, whichutilizes prisms to reduce light reflections at sample cell windowsurfaces, according to the present invention.

FIG. 22 provides a diagram, partly in schematic form, showing anapparatus for mixing the particle dispersion and passing all of saiddispersion through a sample cell in a single pass, according to thepresent invention.

FIG. 23A and FIG. 23B provide block diagrams of systems of analogelectronic modules which implement selection criteria used to determinewhich signal peaks, or portions of the signal peaks, to be utilized inthe particle count data, according to the present invention.

FIG. 24 provides a schematic diagram showing the use of additionallenses to reduce the sensitivity of scattering angle to particleposition, according to the present invention.

FIG. 25 provides graphs showing the particle count probability functionsin linear and logarithmic signal space, the graphs showing the creationof shift invariant functions and a convolution relationship for countdistributions as a function of the logarithm of a scattering signal,according to the present invention.

FIG. 26 provides a graph showing an example of scatter signal responsein two dimensions, where each dimension is a function of the logarithmof the scatter signal, according to the present invention.

FIG. 27 shows details of the graph of FIG. 26, illustrating limits inthe two dimensional space for separation of particles from non-particleevents.

FIG. 27 a provides a graph showing the scatter signal responses in twodimensions for particles of two different types, according to thepresent invention.

FIG. 28 provides a graph showing noise events which are rejected fromthe count distribution, according to the present invention.

FIG. 29 provides a schematic diagram of an optical system, used in thepresent invention, the system measuring scattered light in each of twoscattering planes, the diagram showing the optics of one scatteringplane.

FIG. 30 provides a diagram showing the orientation of the two scatteringplanes for the system shown in FIG. 29.

FIG. 31 provides a diagram showing the scattering plane orientations foran optical system, similar to that shown in FIG. 29, with threescattering planes.

FIG. 32 provides a schematic diagram of an optical system which measuresscattered light in multiple scattering planes by utilizing multipledetector elements, according to the present invention.

FIG. 33 provides a diagram showing an example of detector elementstructure for the system of FIG. 32.

FIG. 34 provides a schematic diagram of a combination of themultiple-element detector systems, such as shown in FIG. 32 or FIG. 33,with the optical system of FIG. 11.

FIG. 35 provides a schematic diagram of a variation of the system shownin FIG. 1, where the signal oscillation is provided by a mask or targetpattern, without interferometric mixing of source and scattered light.

FIG. 36 provides a graph containing plots of examples of three ratios,between four scatter measurements, as a function of particle diameter,according to the present invention.

FIG. 37 provides a schematic diagram of an optical system whichdetermines the position where the particle passes through the lightbeam, according to the present invention.

FIG. 38 provides a schematic diagram of an alternative to FIG. 1, whereall beams are nearly collimated in the regions of the beamsplitters.

FIG. 39 provides a graph showing a functional relationship between thelogarithm of a scattering signal value and the ratio of signal values,measured in two ranges of scattering angle, for various particlediameters, according to the present invention.

FIG. 40 provides a schematic diagram of an optical system which reducesreflection losses at the window surfaces of a particle dispersion samplecell, according to the present invention.

FIG. 41 provides a schematic diagram of an optical system which utilizesmask openings to define interaction volumes of various sizes, accordingto the present invention.

FIG. 42 provides a schematic diagram of an optical system which utilizesdetector elements with different angular weighting functions, accordingto the present invention.

FIG. 43 provides a schematic diagram of an optical system withmulti-element detectors which only receive scattered light from a smallvolume of particle dispersion, according to the present invention.

FIG. 44 provides a diagram showing an example of multi-element detectorswith different angular weighting functions and additional detectorelements for detecting the position of each particle relative to bestfocus of the light beam, according to the present invention.

FIG. 45 provides a diagram showing the interaction volume and scatteringvolumes associated with the concept of FIG. 44.

FIG. 46 provides a block diagram showing analog electronics fordetermining pulse correlation by multiplying scatter signals, used inthe present invention.

FIG. 47 provides a block diagram of a system for measurement of timedelay between two scatter signal pulses, according to the presentinvention.

FIG. 48 provides a diagram showing an apparatus for removing particlesfrom regions, of the light beam and scattered light rays, which are farfrom the interaction volume, according to the present invention.

FIG. 49 provides a schematic diagram of an optical system which measuresthe 2-dimensional scattering distribution and image of each particle,wherein an upstream optical system adjusts this optical system for thecharacteristics of each particle, according to the present invention.

FIG. 49 a provides a schematic diagram of an optical system whichmeasures the 2-dimensional scattering distribution and image of eachparticle, with an analog version of laser power control by an upstreamoptical system, according to the present invention.

FIG. 50 provides a diagram of a rectangular aperture for defining aninteraction volume and a multi-element detector for determining theposition where the particle passes through the light beam, according tothe present invention.

FIG. 51 provides a schematic diagram of an optical system which usesmultiple detector arrays, with different scattering angle scales, toextend the particle size range, according to the present invention.

FIG. 52 provides a schematic diagram showing multiple planes, in anoptical system, where an aperture would eliminate scattered light fromparticles passing through portions of the light beam with poor intensityuniformity, according to the present invention.

FIG. 53 provides a schematic diagram of an optical system which measuresthe angular distribution of scattered light with detector arrays in theback focal plane of the scatter light collection lens, according to thepresent invention.

FIG. 54 provides a block diagram showing an example of a detector arrayand electronics for measuring scatter signals from individual particlesand a particle ensemble, according to the present invention.

FIG. 55 provides a schematic diagram of an optical system which combinesdynamic light scattering and angular light scattering measurements,according to the present invention.

FIG. 56 provides a graph showing the intensity distribution across thewidth of an optical beam and the portion of the beam which is passed byan aperture, according to the present invention.

FIG. 57 provides a graph showing a count distribution, indicating theportion of the count distribution which is removed by an aperture,according to the present invention.

FIG. 58A provides a graph showing two scatter signals, the first signal(S0) showing attenuation of the light beam due to particle scatter, andthe second signal (S1) showing a signal from a detector receivingscattered light from a particle, according to the present invention.

FIG. 58B provides a graph showing two signals produced after the firstsignal in FIG. 58A is modified to produce a signal which increases withthe scattered light.

FIG. 59 provides a graph showing the ratio of values from FIG. 58B as afunction of particle diameter.

FIG. 60 provides a graph showing count distribution as a function of alogarithm of scatter signal, or scatter parameter, for two differentparticle sizes, the functional shapes demonstrating the shift-invariantimpulse response, according to the present invention.

FIG. 61 provides a graph showing the response region limits for atwo-dimensional scatter plot, of counted events, as a function of thelogarithms of two scattering signal values, wherein the functionalshapes demonstrate the two-dimensional shift-invariant impulse responsefor particles of two different diameters, according to the presentinvention.

FIG. 62 provides a graph showing a scatter plot of signal events, asdescribed in FIG. 61, wherein particle scatter impulse response regionlimits and noise events are indicated.

FIG. 63 provides a block diagram of a detector array and electronics formeasuring scatter signals from individual particles and a particleensemble, by utilizing high pass filters, according to the presentinvention.

FIG. 64 provides a schematic diagram of an optical system which combinesparticle settling, ensemble angular scattering, and dynamic lightscattering, according to the present invention.

FIG. 65 provides a schematic diagram of a modification of FIG. 14, whichprovides measurement of scatter from various scatter planes by utilizingat least one rotating scattering plane mask.

FIG. 66 provides a diagram of a periodic mask for producing anoscillating scatter signal, according to the present invention.

FIG. 67 provides a schematic diagram of an optical system whichmultiplexes a detector array between two light sources, where one sourceis utilized for measuring the light beam attenuation due to lightscattered by particles, according to the present invention.

FIG. 68 provides a schematic diagram of an optical system whichmultiplexes a detector array between two light sources, where one sourceis utilized for measuring the light scattered by particles, according tothe present invention.

FIG. 69 provides a schematic diagram of an optical system schematicdiagram, which shows more details of FIG. 67 and FIG. 68.

FIG. 70 provides a schematic diagram of an optical system schematicdiagram, depicting a variation of the optical system in FIG. 69.

FIG. 71 provides a graph of three overlapping signal pulses and the sumof those three signals as measured by a detector, according to thepresent invention.

FIG. 72 provides a graph of the sum of those three signals of FIG. 71,and the signal which results from deconvolution of said sum of threesignals.

FIG. 73 provides a graph showing the original set of three overlappingsignal pulses and the signal, which results from deconvolution of saidsum of three signals, according to the present invention.

FIG. 74 provides a schematic diagram of a scatter plane of an opticalsystem, which is repeated in multiple scattering planes to determine theshape of a particle, according to the present invention.

FIG. 75 provides diagrams of three variations of particle sample cells.

FIG. 76 provides a diagram showing detector elements for measuring theshape of a particle, according to the present invention.

FIG. 77 provides a diagram showing the orientation of detector elementsfor the optical system of FIG. 74, when measuring scattered light inthree ranges of optical scattering planes.

FIG. 78 provides a schematic diagram of an optical system, whichmeasures low angle scatter with a lens, and high angle scattering with aperforated concave mirror, according to the present invention.

FIG. 79 provides a diagram showing an array of detector elements oroptical elements which measure scattered light in multiple ranges ofscatter planes and scattering angles, according to the presentinvention.

FIG. 80 provides a diagram showing an array of detector elements oroptical elements which measure scattered light in multiple ranges ofscatter planes and scattering angles, where each group of scatteringplanes is further divided into ranges of scattering angle, according tothe present invention.

FIG. 81 a provides a front view of the array of FIG. 80, utilizingdiffractive optical elements.

FIG. 81 b provides a side view of the array of FIG. 81 a.

FIG. 82 provides an optical schematic diagram of the diffractive opticof FIGS. 81 a and 81 b, as used to separate and distribute scatteredlight among a group of fiber optics.

FIG. 83 provides diagrams showing the use of two quadrant detectors andmasks to separately measure scattered light in eight different ranges ofscattering planes, according to the present invention.

FIG. 84 provides a diagram of a diffractive optic, where differentsegments consist of linear diffractive gratings, the diagram showingthree different center scattering planes, wherein each center scatterplane is the center of a wedge which collects scattered light from arange of scattering planes, according to the present invention.

FIG. 85 provides an optical schematic diagram of a hybriddiffractive/conventional lens system, which utilizes diffractive opticsas shown in FIG. 84.

FIG. 86 provides a diagram of an optical element which includes multipleannular regions, each with a different diffractive grating, according tothe present invention.

FIG. 87 provides a schematic diagram of an optical system, whichutilizes two masks and two optical arrays, or diffractive optics,according to the present invention.

FIG. 88 provides a graph showing an example of a radial transmissionfunction for an optical mask, according to the present invention.

FIG. 88 a provides a graph which plots the total count distribution andthe measured count distributions from two different sized interactionvolumes, according to the present invention.

FIG. 89 provides a graph which plots ratios of scatter parameters as afunction of center scattering plane orientation, according to thepresent invention.

FIG. 90 provides a graph showing plots of ratios of scatter parametersas a function of center scattering plane orientation for a particle withmore than two dimensions, according to the present invention.

FIG. 91 provides a graph which plots beat frequency factor contours as afunction of scattering angle, and the angle between the motion directionand the light beam, according to the present invention.

FIG. 92 provides a graph which plots beat frequency factor as a functionof scattering angle for an angle of 1 degree between the motiondirection and the light beam, according to the present invention.

FIG. 93 provides a schematic diagram of an optical system, whichprovides an upstream scatter detection system to determine the expectedscatter signal level for the primary scatter system for each particle,according to the present invention.

FIG. 94 provides a graph showing plots of scattered flux in 3 narrowscattering angle ranges, with wedge shaped zones or segments, accordingto the present invention.

FIG. 95 provides a graph showing plots of scattered flux in 3 broadscattering angle ranges, with wedge shaped zones or segments, accordingto the present invention.

FIG. 96 provides a schematic diagram of a variation of the opticalsystem shown in FIG. 78, which provides heterodyne detection andmeasures scattered light over multiple scattering angle ranges and inmultiple scattering planes.

FIG. 97 provides a schematic drawing of a variation of the opticalsystem shown in FIG. 78, which provides an oscillating scatter signal byproducing an interference pattern in the interaction volume.

FIG. 98 provides a graph showing plots of beat frequency factor as afunction of scattering angle for angles of 30, 35, and 40 degreesbetween the motion direction and the light beam, according to thepresent invention.

FIG. 99 provides a graph showing plots of beat frequency factor as afunction of scattering angle for angles of 1 and 90 degrees between themotion direction and the light beam, according to the present invention.

FIG. 100 provides a schematic diagram of an optical system whichmeasures angular scattering distribution from a particle dispersion in asample cell, wherein optical alignment is maintained by aretro-reflector, according to the present invention.

FIG. 101 provides a graph showing plots of an envelope function andheterodyne signal, which comprises a train of oscillations which areamplitude modulated by an envelope determined by the intensity profileof the incident light beam, according to the present invention.

FIG. 102 provides a graph showing plots of low angle scatter, high anglescatter, and the ratio of these values as a function of the scatteringplane angle, for a rectangular shaped particle, according to the presentinvention.

FIG. 103 provides a graph showing plots of low angle scatter, high anglescatter, and the ratio of these values as a function of the scatteringplane angle, for a triangle shaped particle, according to the presentinvention.

FIG. 104 provides a schematic diagram of a sample cell with transparentcones, which reduce unwanted light scattering from outside of theinteraction volume, according to the present invention.

FIG. 105 provides a diagram showing the dimensions and orientation of arectangular particle, as used in the present invention.

FIG. 106 provides a schematic diagram illustrating the use of detectorsize to define the angular range of each detector in FIG. 1.

FIG. 107 provides a schematic diagram of a particle sample system whichadjusts particle concentration to an optimum value, according to thepresent invention.

FIG. 108 provides diagrams showing two window positions for a particledispersion sample cell with adjustable pathlength, according to thepresent invention.

FIG. 109 provides diagrams showing two window positions for a particledispersion sample cell, with adjustable pathlength, which utilizes aflexible diaphragm, according to the present invention.

FIG. 110 provides diagrams showing front and top views of the device ofFIG. 109.

FIG. 111 provides a diagram showing modifications to sample cell windowsto allow larger particles to pass around the interaction volume and toreduce unwanted light scattering from outside of the interaction volume,according to the present invention.

FIG. 112 provides a schematic diagram of a modification to FIG. 14,which provides measurement of scattered light from selected scatterplanes by utilizing at least one scattering plane mask.

DETAILED DESCRIPTION OF THE INVENTION

This application describes an instrument for measuring the sizedistribution of a particle sample by counting and classifying particlesinto selected size ranges. The particle concentration is reduced to thelevel where the probability of measuring scattering from multipleparticles at one time is reduced to an acceptable level. A light beam isfocused or collimated through a sample cell, through which the particlesflow. As each particle passes through the beam, it scatters, absorbs,and transmits different amounts of the light, depending upon theparticle size. So both the decrease in the beam intensity, due to lightremoval by the particle, and increase of light, scattered by theparticle, may be used to determine the particle size, to classify theparticle and count it in a certain size range. If all of the particlespass through a single beam, then many small particles must be countedfor each large one because typical distributions are uniform on aparticle volume basis, and the number distribution is related to thevolume distribution by the particle diameter cubed. This large range ofcounts and the Poisson statistics of the counting process limit the sizedynamic range for a single measurement. For example, a uniform particlevolume vs. size distribution between 1 and 10 microns requires that onethousand 1 micron particles be measured for each 10 micron particle. ThePoisson counting statistics require 10000 particles to be counted toobtain 1% reproducibility in the count. Hence one needs to measure morethan 10 million particles. At the typical rate of 10,000 particles persecond, this would require more than 1000 seconds for the measurement.In order to reduce the statistical count uncertainties, large counts ofsmall particles must be measured for each large particle. This problemmay be eliminated by flowing portions of the sample flow through lightbeams of various diameters, so that larger beams can count large countlevels of large particles while small diameter beams count smallerparticles without the small particle coincidence counts of the largebeam. Accurate particle size distributions are obtained by usingmultiple beams of ever decreasing spot size to improve the dynamic rangeof the count. The count vs. size distributions from each beam are scaledto each other using overlapping size ranges between different pairs ofbeams in the group, and the count distributions from all of the beamsare then combined.

Light scattered from the large diameter beam should be measured at lowscattering angles to sense large particles. The optical pathlength ofthis beam in the particle sample must be large enough to pass thelargest particle of interest for that beam. For small particles, theinteraction volume in the beam must be reduced along all three spatialdirections. The beam crossection is reduced by an aperture or byfocusing the beam into the interaction volume. The interaction volume isthe intersection of the particle dispersion volume, the incident lightbeam, and viewing volume of the detector system. When the particledispersion volume is much larger than the light beam and detectorviewing volume, the interaction volume is the intersection of theincident light beam and the field of view for the detector whichmeasures scattered light from the particle. However, for very smallparticles, reduction of the optical path along the beam propagationdirection is limited by the gap thickness through which the sample mustflow. This could be accomplished by using a cell with variouspathlengths or a cell with a wedge shaped window spacing (see FIG. 9 a)to provide a range of optical pathlengths. Smaller source beams wouldpass through the thinner portions of the cell, reducing the intersectionof the incident beam and particle dispersant volume to avoid coincidencecounts. The other alternative is to restrict the field of view of thescattering collection optics so as to only detect scatterers in a verysmall sample volume, which reduces the probability of multiple particlesin the measurement volume. So particularly in the case of very smallparticles, a focused laser beam intersected with the limited field ofview of collection optics must be used to insure single particlecounting. However, this system would require correction of larger beamsfor coincidence counts based upon counts in smaller beams. To avoidthese count errors, this disclosure proposes the use of a smallinterrogation volume for small particles, using multiple scatteringangles, and a 2 dimensional detector array for counting large numbers ofparticles above approximately 1 micron at high speeds.

Three problems associated with measuring very small particles arescattering signal dynamic range, particle composition dependence, andMie resonances. The low angle scattered intensity per particle changesby almost 6 orders of magnitude between 0.1 and 1 micron particlediameter. Below approximately 0.4 micron, photon multiplier tubes (PMT)are needed to measure the minute scattered light signals. Also thescattered intensity can change by a factor of 10 between particles ofrefractive index 1.5 to 1.7. However, the shape of the scatteringfunction (as opposed to the amplitude) vs. scattering angle is a clearindicator of particle size, with very little refractive indexsensitivity. This invention proposes measurement of multiple scatteringangles to determine the size of each individual particle, with lowsensitivity to particle composition and scattering intensity. Sincemultiple angle detection is difficult to accomplish with bulky PMT's,this invention also proposes the use of silicon photodiodes andheterodyne detection, in some cases, to measure low scattered signalsfrom particles below 1 micron. However, the use of any type of detectorand coherent or non-coherent detection are claimed.

Spherical particles with low absorption will produce a transmitted lightcomponent which interferes with light diffracted by the particle. Thisinterference causes oscillations in the scattering intensity as afunction of particle size. The best method of reducing theseoscillations is to measure scattering from a white light or broad bandsource, such as an LED. The interference resonances at multiplewavelengths are out of phase with each other, washing out the resonanceeffects. But for small particles, one needs a high intensity source,eliminating broad band sources from consideration. The resonancesprimarily occur above 1.5 micron particle diameter, where the scatteringcrossection is sufficient for the lower intensity of broadband sources.So the overall concept may use laser sources and multiple scatteringangles for particles below approximately 1 micron, and broad bandsources with low angle scattering or total scattering for particle sizefrom approximately 1 micron up to thousands of microns. We will startwith the small particle detection system.

FIG. 1 shows a configuration for measuring and counting smallerparticles. A light source is projected into a sample cell, whichconsists of two optical windows for confining the flowing particledispersion. The light source in FIG. 1 could also be replaced by anapertured light source as shown in FIG. 1A. This aperture, which is inan image plane of the light source, blocks unwanted stray light whichsurrounds the source spot and the aperture can control the spatialintensity distribution of the source in the sample cell by eliminatinglow intensity tails of the distribution. In the case of laser sources,this aperture may be used to select a section of uniform intensity fromthe center of the laser crossectional intensity profile. In all figuresin this disclosure, either source configuration is assumed. The choiceis determined by source properties and intensity uniformity requirementsin the sample cell. So either the light source, or the apertured imageof the light source, is collimated by lens 101 and a portion of thiscollimated beam is split off by a beam splitter to provide the localoscillator for heterodyne detection. While collimation between lenses101 and 102 is not required (eliminating the need for lens 102), itprovides for easy transport to the heterodyne detectors 112 and 113.Lens 102 focuses the beam into a two-window cell as a scattering lightsource for particles passing through the cell. The scattered light iscollected by two optical systems, a high angle heterodyne system forparticles below approximately 0.5 microns and a low angle non-coherentdetector for 0.4 to 1.2 micron diameter particles. Each system hasmultiple detectors to measure scattering at multiple angles. FIG. 1shows a representative system, where the representative approximate meanscattering angles for detectors 110, 111, 112, and 113 are 10, 20, 30,and 80 degrees, respectively. However, other angles and numbers ofdetectors could be used, including more than 2 detectors for each oflens 103 or lens 104. All four scattering intensity measurements areused for each particle passing through the intersection of the field ofview of each of the two systems with the focused source beam. Detectors110 and 111 use non-coherent detection because the signal levels for thelarger particles measured by these two detectors are sufficiently largeto avoid the complexity of a heterodyne system. Also the Dopplerfrequency for particles passing through the cell at meter per secondspeeds are too low to accumulate many cycles within the single particlepulse envelope at these low scattering angles. The Doppler frequenciesmay be much larger at larger scattering angles where the heterodynedetection is needed to measure the small scattering intensities fromsmaller particles.

Lens 104 collects scattered light from particles in the flowingdispersant. Slit 114 is imaged by lens 104 into the cell. Theintersection of the rays passing through that image and the incidentsource beam define the interrogation volume where the particle mustreside to be detected by detectors 110 and 111. Detectors 110 and 111each intercept a different angular range of scattered light. Likewisefor lens 103, slit 115 and detectors 112 and 113. The intersection ofthe rays by back-projection image of slit 115 and the source beam definean interrogation volume for the heterodyne system. The positions of slit114 and slit 115 are adjusted so that their interrogation volumescoincide on the source beam. In order to define the smallest interactionvolume, the images of the two slits should coincide with the minimumbeam waist in the sample cell. These slits could also be replaced byother apertures such as pinholes or rectangular apertures. A portion thesource beam, which was split off by a beamsplitter (the sourcebeamsplitter), is reflected by a mirror to be expanded by a negativelens 105. This expanded beam is focused by lens 106 to match thewavefront of the scattered beam through lens 103. This matching beam isfolded through slit 115 by a second beamsplitter (the detectorbeamsplitter) to mix with the scattered light on detectors 112 and 113.The total of the optical pathlengths from the source beamsplitter to theparticle in the sample cell and from the particle to detectors 112 and113, must match the total optical pathlength of the local oscillatorbeam from the source beamsplitter through the mirror, lenses 105 and106, the detector beamsplitter, and slit 115 to detectors 112 and 113.The difference between these two total optical pathlengths must be lessthan the coherence length of the source to insure high interferometricvisibility in the heterodyne signal. The scattered light is Dopplershifted by the flow velocity of the particles in the cell. By mixingthis Doppler frequency shifted scattered light with unshifted light fromthe source on a quadratic detector (square of the combined E fields), aDoppler beat frequency is generated in the currents of detectors 112 and113. The current oscillation amplitude is proportional to thesquare-root of the product of the source intensity and the scatteredintensity. Hence, by increasing the amount of source light in themixing, the detection will reach the Shot noise limit, allowingdetection of particles below 0.1 micron diameter. By using a sawtoothdrive function to vibrate the mirror with a vibrational componentperpendicular to the mirror's surface, introducing optical phasemodulation, the frequency of the heterodyne carrier can be increased toproduce more signal oscillations per particle pulse. During each rise ofthe sawtooth function and corresponding motion of the mirror, theoptical frequency of the light reflected from the mirror is shifted,providing a heterodyne beat signal on detectors 112 and 113 equal tothat frequency shift. Then the mirror vibration signal could be usedwith a phase sensitive detection, at the frequency and phase of the beatfrequency, to improve signal to noise. This could also be accomplishedwith other types of optical phase modulators (electro-optic andacousto-optic) or frequency shifters (acousto-optic). The referencesignal for the phase sensitive detection could be provided by a separatedetector which measures the mixture of light, which is reflected by themoving mirror (or frequency shifted by another device), with theunshifted light from the source.

For particles above approximately 0.4 microns, signals from all 4detectors will have sufficient signal to noise to provide accurateparticle size determination. The theoretical values for these 4detectors vs. particle size may be placed in a lookup table. The 4detector values from a measured unknown particle are compared againstthis table to find the two closest 4 detector signal groups, based uponthe least squares minimization of the function:

(S1−S1T)̂2+(S2−S2T)̂2+(S3−S3T)̂2+(S4−S4T)̂2

where S1,S2,S3,S4 are signals from the 4 detectors, S1T,S2T,S3T,S4T arethe theoretical values of the four signals for a particular particlesize, and ̂₂ is the power of 2 or square of the quantity preceding thê.

The true size is then determined by interpolation between these two bestdata sets based upon interpolation in 4 dimensional space. The sizecould also be determined by using search algorithms, which would findthe particle size which minimizes the least square error while searchingover the 4 dimensional space of the 4 detector signals. For particles ofsize below some empirically determined size (possibly around 0.4micron), detector 110 and 111 signals could be rejected for insufficientsignal to noise, and only the ratio of the signals (or other function oftwo signals) from shot noise limited heterodyne detectors 112 and 113would be used to size each particle. If the low angle signals fromdetectors 110 and 111 are needed for small particles, they could beheterodyned with the source light using the same optical design as usedfor detectors 112 and 113. In any case, only signals with sufficientsignal to noise should be used in the size determination, which mayinclude only the use of detectors 110 and 111 when detector 112 and 113signals are low. The look up table could also be replaced by an equationin all 4 detector signals, which would take the form of: particle sizeequals a function of the 4 detector signals. These techniques, leastsquares or function, could be extended to more than 4 detectors. Forexample, 3 detectors could be used for each system, discarding the lowangle non-coherent detection when the signal to noise reachesunacceptable levels. In this case, a 6-dimensional space could besearched, interpolated, or parameterized as described above for the 4detector system. This disclosure claims the use of any number ofdetectors to determine the particle size, with the angles andparameterization functions chosen to minimize size sensitivity toparticle composition.

By tracing rays back from slits 114 and 115, the fields of view for twosystems are determined, as shown in FIG. 2. The traced rays and sourcebeam converge into the interrogation volume, where they all intersect.FIG. 2 shows these rays and beam in the vicinity of this intersectionvolume, without detailed description of the converging nature of thebeams. The intersection volume is the intersection of the source beamand the field of view of the detector. In this case, the beam from slit114 may be wider than that from slit 115, so that the source beam andslit 115 field of view fall well within the field of view of slit 114.And the source beam falls well within the field of view of slit 115. Byaccepting only particle signal pulses which show coincidence with pulsesfrom detector 113 (which has the smallest intersection with the sourcebeam, shown by the crosshatched area), the interrogation volume ismatched for all 4 detectors. The source beam could also have arectangular crossection, with major axis aligned with the long axis ofthe slits. This would reduce the edge effects for particles passing nearto the edges of the beam. The slit images are designed to be much longerthan the major axis of the source beam, so that both slits only need tobe aligned in the direction perpendicular to the source major axis. Thisprovides for very easy alignment to assure that the intersection ofimages from detectors 112 and 113 and the source beam fall within theintersection of images from detectors 110 and 111. The slit positioncould also be adjusted along the optical axis of the detection system tobring the crossover point of both detector fields of view to becoincident with the source beam. Another configuration is shown in FIG.2 a, where slit 115 is wider than slit 114. Here detector 111 definesthe smallest common volume as indicated by the cross hatched area. Andso only particles which are counted by detector 111 can be counted bythe other detectors. All other particles detected by the otherdetectors, but not detected by detector 111, are rejected because theydo not produce concurrent signals in every detector. This process can beextended to more than 4 detectors. In some cases three or more detectorsper optical system may be required to obtain accurate size measurement.In this case, the size could be determined by use of a look up table orsearch algorithm.

The data for each particle would be compared to a group of theoreticaldata sets. Using some selection routine, such as total RMS difference,the two nearest size successive theoretical sets which bracket eitherside of the measured set would be chosen. Then the measured set would beused to interpolate the particle size between the two chosen theoreticalsets to determine the size. The size determination is made very quickly(unlike an iterative algorithm) so as to keep up with the large numberof data sets produced by thousands of particles passing through thesample cell. In this way each particle could be individually sized andcounted according to its size to produce a number-vs.-size distributionwhich can be converted to any other distribution form. These theoreticaldata sets could be generated for various particle refractive indices andparticle shapes.

In general, a set of design rules may be created for the intersection offields of view from multiple scattering detectors at various angles. Letus define a coordinate system for the incident light beam with the zaxis along the direction of propagation and the x axis and y axis areboth perpendicular to the z axis, with the x axis in the scatteringplane and the y axis perpendicular to the scattering plane. Thescattering plane is the plane which includes the source beam axis andthe axis of the scattered light ray. In most cases the detector slitsare oriented parallel to the y direction. Many configurations arepossible, including three different configurations which are listedbelow:

-   1) The incident beam is smaller than the high scattering angle    detector field crossection, which is smaller than the low scattering    angle detector field crossection. Only particle pulses that are    coincident with the high angle detector pulses are accepted. The    incident beam may be spatially filtered (FIG. 1A) in the y    direction, with the filter aperture imaged into the interaction    volume. This aperture will cut off the Gaussian wings of the    intensity profile in the y direction, providing a more abrupt drop    in intensity. Then fewer small particles, which pass through the    tail of the intensity distribution, will be lost in the detection    noise and both large and small particles will see the same effective    interaction volume.-   2) The incident beam is larger than the low scattering angle    detector field crossection, which is larger than the high scattering    angle detector field crossection. Only particle pulses that are    coincident with the high angle detector pulses are accepted. The    correlation coefficient of the pulses or the delay (determined by    cross correlation) between pulses is used to insure that only pulses    from particles seen by every detector are counted.-   3) The incident beam width and all fields from individual detectors    progress from small to large size. Then particles counted by the    entity with the smallest interaction volume will be sensed by all of    the rest of the detectors. Only particles sensed by the smallest    interaction volume entity will be counted, because this smallest    interaction volume will be contained in all of the interaction    volumes for the other detectors, which will also see this particle.    For example, if the progression from smallest to largest interaction    volume is low angle to high angle, then only events with a low angle    scattering pulse will be accepted.-   4) In all cases, the slits could be replaced by rectangular    apertures, which would remove spurious scattering and source light    components which are far from the interaction volume.

When the beam is larger than the detector fields of view, good intensityuniformity is obtained in the interaction volume. However, then manysignal pulses, which are not common to all detector fields of view, willbe detected and must be eliminated from the count by the methodsdescribed in this application. When the beam is smaller than the fieldsof view, the intensity uniformity is poor, but fewer signal pulses aredetected outside of the common volume of the detector fields. Also thehigher source intensity of the smaller beam provides higher signal tonoise for the scattered light pulses. In this case, the detectorintensity variation can be corrected for by deconvolution methodsdescribed later or reduced by aperture (FIG. 1A for example) of thelight source to select a region of uniform intensity of the lightsource. Each slit (source and detector) could be replaced by arectangular aperture which defines the interaction volume and laser spotin both x and y directions. This would provide the best discriminationagainst spurious scattered light and provide best truncation of thetails of the laser spot intensity distribution. However, thisconfiguration may be more difficult to align. One side of the rectangleshould be oriented parallel to the flow so that particles are eitherentirely in or out of the beam as they pass through the sample cell.This aperture orientation and elimination of intensity tails in thesource intensity distribution (FIG. 1A) will produce signal pulses, onall detectors, which have similar shape for any position of passagethrough the beam. This uniformity of pulse shape is effective indetection of low level pulses in noise. Because the shape and positionof largest signal pulse of the detector set can be used to find thepulse from the detectors with weaker signals, by solving for that shapeand position with an arbitrary background. The pulse height and signalbaseline are determined from the digitized signals using regressionanalysis which assumes the pulse shape of the other stronger signal.This method is also useful when the field of view A, of the smallersignal detector, is larger than the field of view B of the larger signaldetector, and view B is contained inside of view A. Then the smallersignal pulse will have the same shape as the larger signal pulse, duringthe duration of the larger pulse. This larger signal can also bemultiplied times the smaller signal. This signal product wouldaccentuate the correlated portion of the smaller signal. Also the largersignal could be used as a matching filter for the smaller signaldetection. Both of these methods are describe later in this application.

In most cases the divergence of the laser beam should be minimized inthe scatter plane to allow detection of particle scatter at lowscattering angles. Then the laser spot should be wider in the xdirection, and the major axis of the source rectangular aperture (FIG.1A) would be parallel to the x axis to minimize the beam divergence inthat plane. The major axis of the detector rectangular apertures (samelocations as slits 114 and 115 and slits 301 and 302 of FIG. 3 and slits501 and 502 of FIG. 5) could be parallel to the x or y axis. The imageof the detector aperture in the interaction volume should be larger thanthe beam in the y axis, to provide for easy alignment, but restrictivein the x axis to define a small interaction volume. The aperture couldbe smaller than the source beam in both x and y, but with more difficultalignment. If the beam is much larger than the image of the detectoraperture, this alignment difficulty is removed and the intensityuniformity in the interaction volume is improved, but with lower sourceintensity and scattered signal. Pinholes or square apertures could alsobe used in place of slits 114 and 115. In all cases, the intersection ofthe images of both apertures (detector and source for each detector)defines the interaction volume where particle scatter can be detected bythat detector.

The two detector pairs, 1+2 and 3+4, could also be used independently tomeasure count vs. size distributions. The lower angle pair could onlymeasure down to the size where the ratio of their angles is no longersensitive to size and the scattering crossections are too small tomaintain signal to noise. Likewise for the high angle detectors, theycan only measure up to sizes where their ratio is no longer monotonicwith particle size. However, absolute scattered signal levels could beused to determine the particle size outside of this size region. Sinceextremes of these operational ranges overlap on the size scale, the twopairs could be aligned and operated independently. The small angledetectors would miss some small particles and the high angle detectorswould miss some large particles. But the two independently acquiredparticle size distributions could be combined using their particle sizedistributions in the size region where they overlap. Scale onedistribution to match the other in the overlap region and then use thedistribution below the overlap from the high angle detectors for belowthe overlap region and the distribution from the low angle detectors forthe distribution above the overlap region. In the overlap region, thedistribution starts with the high angle result and blends towards thelow angle result as you increase particle size. Detector triplets couldalso be used, where the largest angle of the low angle set and thelowest angle of the high angle set overlap so as to scale the scatteringmeasurements to each other.

In some cases, the angular range of each of the heterodyne detectorsmust be limited by the considerations described later (see FIG. 91 anddiscussion of detector angular widths) to maintain heterodyne signalvisibility.

The flat window surfaces could be replaced by spherical surfaces (seeFIG. 75) with centers of curvature which coincide with the center of theinterrogation volume. Then the focal positions of all of the beams wouldremain in the same location for dispersing liquids with variousrefractive indices. These systems can also be designed using fiberoptics, by replacing beamsplitters with fiber optic couplers. Then thevibrating mirror could be replaced by a fiber optic phase modulator.

FIG. 3 shows an alternate optical configuration for FIG. 1, where thelow angle scattering system is placed on the opposite side of the cellfrom the high angle system. In some cases, this configuration willfacilitate the mechanical design of the support structure for the celland optical systems.

The detector currents from the low angle system and the high anglesystem must be processed differently. Every particle passing through theinteraction volume will produce a pulse in the detector current.Detectors 310 and 311 will show simple pulses, but detectors 312 and 313will produce modulated pulses. The heterodyne detection measures theDoppler beat frequency as the particle passes through the beam. So eachheterodyne pulse will consist of a train of oscillations which areamplitude modulated by an envelope determined by the intensity profileof the incident beam, as shown in FIG. 101 for a Gaussian beam profile.The heterodyne signal must pass through a high pass filter or bandpassfilter (to remove the large local oscillator offset) and then anenvelope detector (see FIG. 4) to remove the heterodyne oscillations,producing the signal envelope for further processing. This preprocessingenvelope detection is used in the process steps below.

For small particles the heterodyne signals will be buried in lasersource noise. FIG. 5 shows an additional detector 505 which measures theintensity of the local oscillator laser noise. If we define a heterodynedetector current as I1 and the detector 505 laser monitor detectorcurrent as I2 we obtain the following equations which hold for each ofthe heterodyne detectors.

I1=sqrt(R*Io(t)*Is(t))*COS(F*t+A)+R*Io

I1=sqrt(R*Io(t)*S(1−R)Io)*COS(F*t+A)+R*Io

I2=K*Io(t)

where:

COS(x)=cosine of x

K is a constant which includes the product of the reflectivities of thebeamsplitter 510 and beamsplitter 513R and (1−R) are the effective reflectivity and transmission of the beamsplitters, respectively

R=R2*R3*(1−R1)

(1−R)=(1−R2)*(1−R3)

R2 is the reflectivity of beamsplitter 512R3 is the reflectivity of beamsplitter 513R1 is the reflectivity of beamsplitter 510

sqrt(x)=square root of x

Io(t) is the source beam intensity as function of time tF is the heterodyne beat frequency at a heterodyne detector due to themotion of the scatterer in the sample cell. And A is an arbitrary phaseangle for the particular particle.Is(t) is the scattered light intensity from the particle:

Is(t)=S*(1−R)*Io(t)

where S is the scattering efficiency or scattering crossection for theparticle

The light source intensity will consist of a constant portion Ioc andnoise n(t):

Io(t)=Ioc+n(t)

We may then rewrite equations for I1 and I2:

I1=sqrt(S*(1−R)*R)*(Ioc+n(t))*COS(F*t+A)+R*(Ioc+n(t))

I2=K*(Ioc+n(t))

The heterodyne beat from a particle traveling with nearly constantvelocity down the sample cell will cover a very narrow spectral rangewith high frequency F. For example, at 1 meter per second flow rate, thebeat frequency would be in the megahertz range. If we use narrow bandfilters to only accept the narrow range of beat frequencies we obtainthe narrow band components for I1 and I2:

I1nb=sqrt(S*(1−R)*R)*Ioc*COS(F*t+A)+R*n(t)

I2nb=K*n(t)

where we have assumed that n(t) is much smaller than Ioc. And also n(t)is the portion of the laser noise that is within the electronicnarrowband filter bandwidth (see below).

The laser noise can be removed to produce the pure heterodyne signal,Idiff, through the following relationship:

Idiff−I1nb−(R/K)*I2nb=Sqrt(R*(1−R)*S)*Ioc*COS(F*t+A)

This relationship is realized by narrowband filtering of each of the I1and I2 detector currents. One or both of these filtered signals areamplified by programmable amplifiers, whose gains and phase shifts areadjustable. The difference of the two outputs of these amplifiers isgenerated by a difference circuit or differential amplifier. With noparticles in the beam, the gain and phase shift of at least one of theprogrammable amplifiers is adjusted, under computer or manual control,to minimize the output of the difference circuit (i.e. (gain forI2)*R/K=1, assuming gain for I1=1) At this gain, the source intensitynoise component in the detector 503 or detector 504 beat signal, withparticles present, is eliminated in the difference signal, which is fedto an analog to digital converter (A/D), through a third narrowbandfilter, for analysis to sense the beat signal buried in noise. Thisfiltered difference signal could also be detected by a phase lockedloop, which would lock in on the beat frequency of current from theheterodyne detector.

The particle dispersion flow rate could also be adjusted to maximize theheterodyne signal, through the electronic narrowband filter, by matchingthe Doppler frequency from flowing particle scattered light with thecenter of the filter bandpass.

This entire correction could also be accomplished in the computer byusing a separate A/D for each filtered signal and generating thedifference signal by digital computation inside the computer. The phaseand gain adjustments mentioned above, without particles in the beam,could be adjusted digitally. Also these gain adjustments could also bedetermined from measurement of the signal offsets I1 dc and I2 dc (theaverage value of the signal due to the local oscillator). If thescattering component of the heterodyne signal is negligible compared tothe offset caused by the local oscillator, this adjustment could bedetermined from measurements taken with particles in the beam. In thiscase, the contribution from the source intensity noise should beproportional to the offset level because the noise is the samepercentage of the average level of the intensity in both I1 and I2. Thenthe coefficient ratio R/K in the equation for Idiff can be calculatedfrom:

R/K=I1dc/I2dc

Where I1 dc and I2 dc are the average of the unfiltered signals I1 andI2, respectively. And the gain (or digital multiplier) of I2 is then I2dc/I1 dc (relative to a gain for signal I1=1).

If both signals were digitized separately, other correlation techniquescould be used to reduce the effects of source intensity noise.Beamsplitter 512 and 513 reflections are adjusted to obtain shot noiselimited heterodyne detection, with excess laser noise removed by thedifference circuit.

The noise correction techniques described on the prior pages (and FIG.5) can be applied to any heterodyning system by simply adjusting thefiltering of currents I1 and I2 to pass the signal of interest, whileblocking the low frequency component (Ioc) of Io(t). Excess laser noiseand any other correlated noise component, which is present in both theheterodyne signal and the light source, can be removed from the signalof interest through this procedure. One application is dynamic lightscattering, where the heterodyne signal is contaminated by laser sourcenoise in the optical mixing process. The filters on I1 and I2 would bedesigned to pass the important portion of the Doppler broadened spectrum(using a lower frequency broad band filter or high pass filter insteadof the high frequency narrow band filter) and to remove the large signaloffset due to the local oscillator. Then by using the subtractionequation described below (where the narrow band filter is replaced bysaid broad band filter in all equations) the effects of laser noise canbe removed from the Doppler spectrum, improving the particle sizeaccuracy.

Idiff−I1nb−(R/K)*I2nb=Sqrt(R*(1−R)*S)*Ioc*COS(F*t+A)

In this case, the heterodyne signal is the sum of many COS functionswith various frequencies and phases. The noise, common to both theheterodyne signal and incident light source intensity, will still becompletely removed in Idiff. In the case of fiber optic heterodyningsystems, the laser monitor current, I2, could be obtained at the exit ofthe unused output port of the fiber optic coupler which is used totransport the light to and from the particle sample, because this portcarries light only from the optical source, without any scattered light.I2 can be measured with a light detector at any point in the opticalsystem where the light source intensity vs. time is available. Thissubtraction shown in the equation above could be accomplished by theanalog difference circuit or by digital subtraction after digitizationof both the filtered contaminated signal and the filtered source monitoras outlined previously. This procedure could also be accomplished usingthe unfiltered signals, but with much poorer accuracy due to the largesignal offsets.

FIG. 6 shows the system with some additional features. The sample cellwindows contain spherical surfaces with center of curvature at theinteraction volume, similar to the concepts shown in FIG. 75. The lightsource beam and detector acceptance cones pass through these sphericalsurfaces in order to avoid focal shift of the source and detector beamswhen the refractive index of the dispersing fluid is changed. Theheterodyne detector currents from detectors 603 and 604 are passedthrough a high pass filter to remove the large local oscillator currentand then (after completing the noise removal described above) they arepassed through an envelope detector to remove the heterodyne oscillationdue to the Doppler shifted spectrum of the scattered light from themoving particles. As mentioned earlier, this Doppler frequency may beincreased by vibrating the mirror so as to add phase modulation to thelocal oscillator. This will provide more signal oscillations per signalpulse. After the high pass or narrowband filter, the signal will consistof a sinusoid which is amplitude modulated by the scattering pulse dueto the particle's transit through the source beam (see FIG. 101). Theenvelope of this modulated sinusoid is measured by an envelope detectoras shown in FIG. 4. The resulting single pulse is digitized by an analogto digital converter (A/D) before analysis by a computer. This processis similar for each of detectors 603 and 604. Since lower anglescattering produces lower Doppler frequency, the lower scattering anglesignals are usually measured without heterodyne detection when thesignals are large. So for large signal levels, Detectors 601 and 602 donot require heterodyne detection; but a heterodyne optical system, asused for detectors 603 and 604, could be used for detectors 601 and 602if the signal levels were small. Then the vibrating mirror phasemodulator, shown in figure below, could be used to increase theheterodyning frequency. If the signals are large, the scattered lightcurrent pulses from detectors 601 and 602 can be digitized directlybefore computer analysis, without envelope detection. The analysis ofthese signals is described below.

One other aspect of this invention is a means for auto-alignment of theoptics. Auto alignment is needed to correct for changes in beamdirection and focus due to changes of dispersant refractive index andmechanical drift of optical components. Auto-alignment could be doneperiodically by the computer or whenever a new particle sample or newdispersing fluid is introduced to the system. These techniques can beused to auto-align any of the apertures, in this application, which arein an image plane of the particle, such as apertures 7802 and 7803 inFIG. 78. As shown in FIG. 2, the source beam and all four fields ofview, from the four detectors, must intersect at the same point to allsee scattering from the same particle. Images of slits 610 and 611define the point where the view fields from each detector pair (1+2 or3+4) intersect. The slit apertures usually only need alignment in onedirection, perpendicular to the slit, but position adjustment may alsobe needed along the optical axis of the detector system to place theintersection between the fields of view from detectors 601 and 602 (or603 and 604) on the source beam. Pinhole or rectangular apertures mustbe aligned in two orthogonal directions which are in the planeperpendicular to the optical axis of the scattering detection opticalsystem. Either one or both slits may be adjusted to obtain alignment.FIG. 5 shows an example where both slit positions are optimized by acomputer controlled micro-positioner. For example, the digitized signalsfrom detector 602 and detector 603 could be digitally multiplied (afterthe envelope detector) and the resulting product integrated or low passfiltered to produce a correlation between the two detector signals. Theposition slit 610 is adjusted until this correlation signal is maximumwith particles flowing through the interaction volume. If needed, bothslits 610 and 611 may be moved to optimize this correlation signal. Ingeneral these should be small adjustments because the spherical windowsurfaces will prevent large beam refractions and focal shifts due tochanging particle dispersant refractive index. In systems with largebeam shifts, the slits may need to be moved perpendicular and parallelto the optical axis of each optical system to maximize the correlationbetween the detectors. This could be accomplished with dual axismicro-positioners, which could also be used when the slits are replacedby pinholes or rectangular apertures, which require alignment in twoorthogonal axes perpendicular to the optical axis of the scatteringdetection optical system.

FIG. 2 shows larger fields of view for detectors 110 and 111 than fordetectors 112 and 113. This is accomplished with slit 610 wider thanslit 611 or by larger magnification for lens 613 than for lens 612(image of the slit in the interaction volume). Hence the alignment ofslit 610 is much less critical then slit 611 because image of slit 610in the interaction volume is wider and has larger depth of focus thanfor slit 611. By placing computer controlled micro-positioners on slit610 and slit 611, the system can be aligned by using the correlationbetween the signals. The micro-positioners move each slit perpendicularto the long axis of the slit opening and perpendicular to the opticalaxis of that lens. The alignment procedure is described below:

-   1) With low concentration of particles in the flow stream, adjust    the position of slit 611 to maximize the correlation (using an    analog multiplier and RMS circuit) between the signals from    detectors 603 and 604. At this point the intersection of the fields    of views of both detectors cross at the incident beam and the    signals are maximum.-   2) Then adjust the position of slit 610 until the correlation of    detectors 601 and 602 with detectors 603 and 604 is a maximum. After    this adjustment both detectors 601 and 602 view the intersection    defined by step 1.

During particle counting and measurement, only particles seen by bothdetectors 603 and 604 are counted by all of the detectors, because theyare a subset of the particles seen by detectors 601 and 602. By usingdifferent slit image sizes and using the smaller slit images todetermine count acceptance, the system will accept only particles whichare seen by all four detectors. If the slit images from detectors 603and 604 are larger than the images from detectors 601 and 602, thendetectors 601 and 602 would be adjusted before adjusting 603 and 604;and detectors 601 and 602 would select which particles are counted. Thegeneral rule is that the detector images which have the smallestintersection with the incident beam are adjusted first and theydetermine which particles will be counted. The slit widths are chosen tocreate one slit image with a small intersection volume and the otherwith a larger intersection volume so that when a particle is detected inthe smaller volume, it is clearly within the larger volume. The smallerslit image only needs to cross the incident beam near to its imageplane. Then the larger slit image only needs to cover the intersectingvolume to insure that it sees all of the particles passing through thesmaller slit image. Then by only counting particles detected by thesmaller slit image, only particles which are seen by both detectors willbe counted. If the slit images were comparable in size, very precisealignment of both slit images with each other would be required and thecorrelation between the detector signals would be needed to choose whichparticles to count. This comparable sized slit case is also claimed inthis disclosure. Also the replacement of slits with rectangularapertures or pinholes is also claimed, but with the requirement for twoaxis alignment as indicated previously.

FIG. 6 a shows an example of scattered detection pulses from the fourdetectors. These signals are measured after a high pass filter for eachof detectors 601 and 602, and after a high pass filter and envelopedetector for each of detectors 603 and 604. The high pass filters couldbe replaced by narrow band filters. This data describes the case wherethe particle passes through a corner of the volume which is common tothe source beam and the field of view from detector 604 (see FIG. 2).Detectors 601, 602, and 603 show similar profiles as a function of timeas the particle passes through the interaction volume. However thesignal from detector four is truncated at the leading edge due to theedge of the detector field of view. Over the region where the particleis well within the detector fields of view, each detector signal willmaintain the same ratio with another detector signal as the detectorsignal amplitudes follow the particle passing through the sourcecrossection intensity distribution. This region of stable signal ratiomust be determined in order to eliminate the effects of the variation insource intensity by ratioing pairs of detector signals. Each of the fourdetector signals is digitized and the ratio of signal from the detectorwith the minimum interaction volume with one of the other detectors iscalculated at each A/D (analog to digital conversion) sampling point.The A/D may be only turned on by a comparator during the period whereall the detector signals are above a noise threshold, between times T1and T2 in FIG. 6 a. In this case the ratio between detectors 603 and 604is used to determine the optimum portion the sampled data to use. Theratio of detector 604/detector 603 increases as the particle enters thefield of view of detector 604. Once the particle is completely insidethe field of view, the ratio between the two signals is nearly constanteven though the individual signals are changing due to the sourceintensity distribution non-uniformity. Eventually, the signal levelsdrop and the signal ratio becomes very noisy. If we assume that thereare 20 samples between T1 and T2, we could measure the variance of theratio for samples 1 through 5 and then the variance of the ratio forsamples 2 through 6, and so on up to samples 16 through 20. The 5 sampleset with the lowest variance for the detector 603/detector 604 ratiowould be chosen to determine the detector to detector ratios for alldetector combinations for that particle, either by choosing the samplein the middle (sample 3) of that set or by averaging all 5 ratios toobtain an averaged ratio for the 5 samples in the set. The assumption of20 samples and 5 samples per set is an example. This invention claimsany appropriate data set size and segmentation.

The pulses shown in FIG. 6 a are the result of some prior electronicfiltering and envelope detection. The signals from detectors 601 and 602will be simple pulses which may be cleaned up by a high pass filterbefore the A/D conversion. The signals from the heterodyne detectors 603and 604 are the product of a pulse and a sinusoid. The pulse may consistof a megahertz sine wave, amplitude modulated by the intensity profileof the source beam over a period of about 100 microseconds, dependingupon the size of the interaction volume and the particle flow velocity.This oscillatory signal sits on top of a large offset due to the localoscillator intensity. This offset and other source noise components maybe removed from the heterodyne signal by high pass or narrow-bandelectronic filtering. The power spectrum of these pulses will reside ina 100 kilohertz band which is centered at 1 megahertz. Hence anarrow-band filter may provide optimal signal to noise for theheterodyne signals. After the filtering, the signals could be digitizeddirectly for digital envelope detection or an analog envelope detectorcould be used to remove the 1 megahertz carrier, reducing the requiredsampling rate to only 10 to 20 samples per pulse instead of 400 samplesper pulse. By using a dual phase lock-in amplifier with referenceoscillator set to the heterodyne frequency (1 megahertz in thisexample), extremely high signal to noise could be obtained by measuringthe filtered signal without the envelope detector. By using the zerodegree and quadrature outputs of the dual phase lock-in amplifier, thephase sensitive signal would be recovered even though the reference andsignal carriers are not necessarily in phase.

The particle counting rate can also be increased by digitizing the peakscattered signal (directly from detectors 601 and 602 and after theenvelope detector from detectors 603 and 604) from each particle insteadof digitizing many points across the scattering pulse and finding thepeak digitally. This is accomplished by using an analog peak detectorwhose output is digitized in sync with the positive portion of thesignal pulse derivative and reset by the negative portion of thederivative. Then only one digitization is needed for each particle, asshown in FIG. 7. The negative comparator switches on when the inputsignal drops below the reference setting and the positive comparatorswitches on when the signal is greater than the reference setting.

Another variation of this concept triggers on the actual signal insteadof the derivative, as shown in FIG. 8. When the signal rises above apreset threshold, the positive comparator takes the peak detector out ofreset mode. As the signal rises, the output of the peak detector (seeFIG. 9) follows the input signal until the signal reaches a peak. Afterthis point, the peak detector holds the peak value with a time constantgiven by the RC of the peak detector circuit. The input signal dropsbelow this as it falls down the backside of the peak. When the signalreaches some percentage of the peak value, the A/D is triggered to readand then reset the positive comparator. This percentage value isprovided by a voltage divider (shown in the figure as 0.5× voltagedivider, but other divider ratios would also be appropriate betweenapproximately 0.2 to 0.8) which determines the reference level for thenegative comparator. The A/D is only triggered once per signal pulse andmeasures the peak value of the pulse. Using this circuit, the detectorwith the smallest interaction volume generates the A/D trigger for allof the other detectors, so that only particles seen by all of thedetectors are counted.

In most cases, the detector signals are either digitized directly, peakdetected with the circuit in FIG. 7 or FIG. 8, or integrated and sampledat a lower rate. The signal can be continuously integrated (up to thesaturation limit of the integrator). Then the integrated signal needs tobe sampled only at points of zero slope in the integrated signal,between each pulse. By subtracting the integrated values on either sideof the pulse, the integral of each pulse is sampled separately withouthaving to sample the pulse at a high sampling rate. Also each pulsecould be sampled at a lower rate and then a function could be fit tothese samples to determine the peak value of the pulse. This should workparticularly well using Gaussian functions which model the intensityprofile of the laser beam. The parameters of the best fit Gaussiansolution directly provides the peak, half width, or integral of thepulse. In any case, the final signal from each pulse will be analyzedand counted. One problem associated with particle counting is theincident beam intensity profile in the interaction volume. Identicalparticles passing through different portions of the beam will seedifferent incident intensity and scatter light proportionally to thatintensity. But the scattered intensity also depends upon the particlediameter, dropping as the sixth power of the diameter below 0.3 microns.So the effective interaction volume will depend upon particle diameterand detection noise, because particles will not be detected below thisnoise level. Therefore small particles will be lost in the noise whenthey pass through the tail of the intensity distribution. This meansthat larger particles have a larger effective interaction volume thansmaller particles and therefore the number distribution is skewed infavor of large particles. This invention includes a method for creatinga particle diameter-independent interaction volume, using signalanalysis. The systems in FIGS. 1, 2, and 3 use at least 2 detectors perscatter collection system to remove the incident intensity dependence byusing the ratio of two scattering angles to determine the particle size.Also for any number of detectors, ratios between any pair of detectorscould be used to determine the size of particles in the size rangecovered by that pair. Instead of detector pairs, detector triplets orquadruplets, etc. could also be used with appropriate equations orlookup tables to determine the size of each particle independent of theincident intensity on the particle. In the case of detector pairs, bothscattered signals, S(A1) and S(A2), are proportional to the scatteringfunction, at that angle, times the incident light intensity:

S(a1)=K*I0*F(D,a1)

S(a2)=K*I0*F(D,a2)

where I0 is the incident intensity, K is an instrumental constant inthis case, and F(D,A) is the scattering per particle per unit incidentlight intensity for a particle of diameter D, at scattering angle a. Thevariable “a” can refer to a single angle or a range of angles over whichthe signal is collected. Then a1 and a2 would refer to the a1 range ofangles and a2 range of angles, respectively. For more than twodetectors, there is a similar equation for each detector signal forangles a1, a2, a3, a4, etc. The scattering signals S(a) may be the pulsepeak value or pulse integral of the envelope of the heterodyne signal(detectors 3 and 4) or of the direct non-coherent signals (detectors 1and 2). So The ratio of the scattering at two angles is equal toF(D,a1)/F(D,a2), which is independent of incident intensity andrelatively independent of position in the Gaussian beam profile of alaser. FIG. 10 shows a conceptual plot of number of particles vs.S(a1)/S(a2) and S(a2). A plot of number of particles vs. S(a1)/S(a2) andS(a1) could also be used. The scattering signal, for any diameter D,will show a very narrow range of S(a1)/S(a2) but a broad range of S(a2).Particles passing through the peak of the laser intensity profile willproduce pulse peak amplitudes at the upper limit, maximum S(a2). Thesurface, describing this count distribution, is determined by fitting asurface function to, or by interpolation of, this count surface in FIG.10. This surface function provides the parameters to determine anaccurate particle count, because S(a1)/S(a2) is a strong function ofparticle size, but a very weak function of particle path through thebeam. By setting an acceptance threshold for S(a2) at a certainpercentage of this maximum value, separately at each value ofS(a1)/S(a2), only particles passing through a certain volume(independent of particle size) of the beam will be accepted and counted.Because the particles, which are counted by these detectors, are allmuch smaller than the source beam crossection, they all have the sameprobability functions for describing the percentage of particles passingthrough each segment of the beam. Therefore, at any value ofS(a1)/S(a2), the shape of the count vs. S(a2) function is nearlyidentical when you normalize the function to maximum S(a2). By setting acount-above threshold at a certain percentage of maximum S(a2) (but wellabove the noise level) at each value of S(a1)/S(a2), only particlespassing through a certain portion of the interaction volume, withacceptable signal to noise, will be counted and sized, as shown in FIG.10 a. The noise threshold is chosen so that all particles with signalsabove that level will be accurately sized based upon the scatteringsignals.

This analysis is usually done for the detector with the smallestinteraction volume, the heterodyne system in the case of FIG. 1. Allfour detectors are used to determine the particle diameter, but theacceptance criteria is determined by only detector 112 and 113(S(a1)=detector 112 and S(a2)=detector 113). This analysis can also beperformed, individually, on any pairs of signals, as long as the noisethreshold is always the same percentage of the maximum value of signalused for the horizontal axis in FIG. 10 a. These counts are accumulatedinto a set of size ranges, each range defines a different size channel.In many cases, each size range has a very narrow width in size andS(a1)/S(a2). The optimum channel size width is the minimum width whichstill contains sufficient particle counts in that channel to avoidstatistical errors. Hence, the distribution of S(a2) for the range ofS(a1)/S(a2) within a certain channel can determine the S(a2) acceptancelimit for counts in that channel. This is accomplished by only countingparticles with S(a2) above a certain percentage of the maximum S(a2) forthat channel. If the theoretical scattering efficiency changessubstantially across any channel, the S(a) for each count is divided bythe theoretical scattering efficiency indicated by the sizecorresponding to the S(a1)/S(a2) for that particle. This may beespecially important below 0.4 microns where the scattering efficiencydrops as the inverse of the sixth power of the particle diameter.

The shape and width of the S(a2) profile is determined by how sharplythe source crossectional intensity distribution drops off at the edgesof the beam. If the beam profile was a step function, the effectiveinteraction volume would be only weakly particle size dependent near theedges. This shape can be accomplished by spatially filtering the source,with the spatial filter aperture in a plane conjugate to the interactionvolume. Then an image of the aperture, which is smeared by aberrationsand diffraction limits, defines the sharpness of intensity drop at theedges of the beam. The intensity tails of the Gaussian beam are cut offby the aperture, which could be sized to cut off at any appropriatepercentage of the peak intensity to limit the variation of scatteringfrom a particle as it traverses the beam. The beam crossectionalintensity distribution may also be shaped by use of appropriateapodization of the beam or by using diffractive beam shapers.

FIG. 10 a describes this concept for data collected in one size channel.The pulse signal is collected and stored for each pulse above the countnoise threshold. But only pulses which are within the range ofS(a1)/S(a2) for that channel are collected into that channel. Thefrequency distribution of counts at each pulse level is plotted for abeam with a Gaussian intensity profile. The problem is that someparticle pulses fall below the noise threshold and are not counted. Theamount of missed particles depends upon the scattering efficiency of theparticles. For smaller particles with lower scattering efficiency, ahigher percentage of particles will be lost below the noise threshold.So the count error will be particle size dependent. The source beam canbe spatially filtered to cut off the low intensity wings of the sourceintensity distribution. Then the count distribution would be as shown inthe “with aperture (ideal)” curve and no particles would be lost in thenoise. This could be accomplished by using a rectangular spatial filterthat cut the wings off in the Y direction, because the particle flows inthe XZ plane and the tails in this plane are actually measured in eachpulse shape. However, the image of the spatial filter aperture in theinteraction volume will be aberrated and diffraction limited as shown bythe “with aperture (aberrated)” curve. In this case a few particles maystill be lost in the noise and a count threshold must be set above thislevel to reject all questionable particle pulses. The maximum S(a2)value changes in each channel due to the change in scattering efficiencyfor the particles in that channel. As long as the count threshold is setto be the same percentage of that maximum S(a2) for each channel, allchannels will lose the same percentage of particles and the distributionwill be correct. Without this channel specific threshold, the smallerparticle channels will lose a larger percentage of particles than thelarger particle channels and the distribution will be skewed towardslarger particles. This assumes that the sample is a homogeneous mixtureof all the particle sizes and that the sufficient count exists in eachchannel to obtain an accurate estimate of the maximum S(a2).

The method described above handles the variations caused by the particlepassing through various random paths in the interaction volume. Thismethod can also correct for the variations due to random positions alongthe path where the digitization occurs. Therefore the peak detectors orintegrators could be eliminated. The signal from the envelope detector(detectors 3+4) and direct signals from detectors 1+2 could be digitizeddirectly at approximately 3 points per pulse. The maximum signal datapoint from each pulse would be added to the data list for input to theanalysis described above. Any deviation from the peak value would not bea problem because the ratio of the signals determines the size and allfour detectors will be low by the same percentage if they are notsampled at the peak intensity position in the interaction volume.

Also all the signals could be digitized directly after the high pass (ornarrow band) filter on the detectors (detectors 112 and 113 are highpass filtered to remove local oscillator current and detectors 110 and111 could also be high pass filtered to remove low frequency noise).Then all of the analog and digital operations (phase sensitivedetection, envelope detection, etc.) could be done digitally but at thecost of reducing data collection rates. Also the source could bemodulated for detectors 110 and 111 to use phase sensitive detection(lock-in amplifier) when their signals are low.

All of the optical design and algorithm techniques described in thisdisclosure may leave some residual size response broadening which may beparticle size dependent. This instrument response broadening isdetermined by measuring a nearly mono-sized particle sample (such aspolystyrene spheres). For example, due to noise or position dependencein the beam, a certain size particle will produce a range of S(a1)/S(a2)values as it repeatedly passes through different portions of theinteraction volume. In any event, the broadening may be removed bysolving the set of equations which describe the broadening phenomena. Ifthe broadening is relatively the same for all size particles, theresponse broadening can be described by a convolution of the broadenednumber distribution response and the actual number vs. sizedistribution. Iterative deconvolution algorithms may be used todeconvolve the measured number vs. measured parameter distribution toobtain size resolution enhancement. This resolution enhancement willwork for any ergodic stochastic process, where the broadening statisticsare stable over time. This idea could be applied to (and is claimed for)any broadened counting phenomena with stable stochastic or deterministicbroadening mechanisms. In particle counting measurements the amount ofscatter from a particle may vary due to the random orientation andposition of a particle as it passes through the exciting light beam, orby other structural and optical noise sources. The counting andclassification of each of a group of identical particles will notproduce a narrow peak when plotting count number vs. measured parameter.Here “measured parameter” refers to the parameter which is measured fromeach particle to determine its size. Examples of measured parameters arescattering optical flux amplitude, ratio of flux from two scatteringangles, a function of fluxes from multiple scattering angles, or thedecrease in intensity due to particle scattering and absorption, as willbe described later in this disclosure. The peak of thenumber-vs.-measured parameter function from a group of monosizedparticles will be broadened in a predictable way. This broadening can bedetermined experimentally with a calibrated group of particles (bymeasuring the response from monosized particle samples) or it can becalculated theoretically based upon models for the random anddeterministic broadening sources. Then the entire system can be modeledusing a matrix equation, where each column in the matrix is thebroadened measured parameter distribution from a certain sized particle.This broadening is reproducible as long as a large number of particlesare counted for each trial. The matrix equation is described by thefollowing relationship:

Nm=M*N

Where Nm is the vector of values of the measured (broadened)number-vs.-measured parameter distribution and N is the vector of valuesof the actual particle number-vs.-size distribution which would havebeen measured if the broadening mechanisms were not present. “*” is amatrix vector multiply. The number distribution is the number ofparticles counted with parameter amplitudes within certain ranges. It isa differential distribution which describes counts in different channelsor bins, each bin with a different range of parameter, which may besize, scattering ratio, etc. M is a matrix of column vectors with valuesof the broadened number-vs.-measured parameter function for eachparticle size in N. For example, the nth column of M is a vector ofvalues of the entire measured number-.vs.-measured parameterdistribution obtained from a large ensemble of particles of the sizewhich is represented by the nth element of vector N. This matrixequation can be solved for the particle number-vs.-size distribution, N,by matrix inversion of M or by iterative inversion of the matrixequation. This particle number-vs.-size distribution can be determinedby using this matrix equation in many different forms. The term“measured parameter” in this paragraph can refer to many size dependentparameters including: scattering signal amplitude (pulse peak orintegral, etc.), the ratio (or other appropriate mathematicalrelationship) between scattered signals at two or more different angles,or even particle diameter (a broadened particle size distributiondetermined directly from a broadened process can also be “unbroadened”by using broadened particle size distributions for each monosized samplecolumn in matrix M). So we solve for N, given Nm and M.

If each column of M is simply a shifted version of the prior column,then the instrument response is shift invariant and the relationship isa convolution of N with the system impulse response IMP:

Nm=IMP**N

where ** is the convolution operator

For this case, deconvolution algorithms may be used to solve for N,given Nm and IMP.

The generalized matrix equation above may also include the effects ofcoincidence counting. As discussed earlier, over one million particlesshould be counted for a uniform volume distribution to be accuratelydetermined in the large particle region. In order to insure lowcoincidence counts, the source spot size in the interaction region mightbe reduced to approximately 20 microns in width so that the particleconcentration can be raised to count 1 million particles at flow ratesof 1 meter per second in a reasonable time. For example, the worst caseis slit 1 being the largest slit, because then the largest interactionvolume might be approximately 20 micron x 20 micron×200 micron, forexample. If we require approximately 5 volumes per particle to avoidcoincidence counts then the inter-particle spacing is 74 microns. 1million particles spaced by 74 microns (on average) moving at 1 meterper second will take 74 seconds to measure. This spot size would providegood count reproducibility for the worst case of uniform volumedistribution. However, a 20 micron spot and the corresponding detectorfields of view may be difficult to align, requiring larger source spotsize with a higher coincidence level. Even with a 20 micron spot, somecoincidences will be seen at the 74 micron particle spacing. Thesecoincidences can be corrected for by including their effects in thegeneralized matrix equation. If M were correcting for coincidences, acolumn in matrix M which corresponds to the large size end of vector Nwill have negative values in the region corresponding to the small sizeend of vector Nm, because the larger particles will block the scatteredlight from smaller particles which are ahead or behind that largerparticle in the source beam. Also a column in matrix M which correspondsto the small size end of vector N will have a tail of positive values inthe region corresponding to the large size end of vector Nm, becausesome smaller particles will be counted coincidentally with the largerparticles and increase their measured size relative to their actualsize. The effects of coincident counts can be mitigated by using a wedgeshaped cell as shown in FIG. 9 a. The cell consists of two windows at anangle so as to produce regions of different optical path along the cell.This cell could replace the cells in FIGS. 11 and 12. The dashed linerays define the edges of the source beam. Then at any point along thewedge direction, only particles smaller than a certain size may passthrough that portion of the cell. The size distributions gathered atdifferent points along the wedge, from the 2 dimensional detector arrayin FIGS. 11 and 12, may be combined by correcting the count in thelarger particle areas for coincidentally counted smaller particles byusing counts in the smaller particle regions of the wedge. Thiscorrection can be accomplished by solving a matrix equation of the formshown previously.

The correction for coincidences may also be accomplished by an iterativeprocedure, which solves for N, given Nm, and then corrects eachscattered signal for coincidences. Each scattered signal, S1 and S2,consists of light scattered (or light lost due to absorption orscattering) from all the particles in the interaction volume. Ideally,the particle concentration is low and most of the time each scatteringevent is from a single particle. But for the general case, multiplecoincident particles can be modeled by the following equation:

Ai=SUMj(G(Ni,Nj)Aj)

where SUMj means summation over the j index. Ai is the “particle signal”for a particle of the ith size bin in the particle size distribution.Particle signals can include S1, S2, or the log of attenuation orobscuration (described later in this disclosure) due scattering andabsorption of a particle. G(Ni,Nj) is a function which describes themost probable total particle signal from a combination of particles ofith and jth sizes based upon their particle numbers (or concentrations),Ni (for the ith size) and Nj (for the jth size). Since the combinationof particles in the interaction volume is a random process, G(Ni,Nj)represents the sum of all combinations (given Ni and Nj), weighted bytheir probability functions.

In the case of signals S(a1) and S(a2), the procedure for determiningthe number vs. size distribution is the following:

-   1) Use the surface plot of FIGS. 10 and 10 a to determine the raw    number distribution Nm.-   2) Solve the matrix equation Nm=M*N for the true number distribution    N.-   3) Recalculate S(a1) and S(a2) using the equation above and the    distribution N:

S(a1)i=SUMj(G1(Ni,Nj)S(a1)j)

S(a2)i=SUMj(G2(Ni,Nj)S(a2)j)

-   4) Do steps 1 through 3 again-   5) repeat iteration loop of step 4 until the change in number    distribution N between successive loops is below some threshold.

For particles between approximately 1 and 10 microns, the ratio ofscattered intensities at two angles below approximately 3 degreesscattering angle is optimal to provide highest size sensitivity andaccuracy. A white light source or broad band LED should be used toreduce the Mie resonances for spherical particles. Above 10 microns, themeasurement of total scatter from a white light source provides the bestsize sensitivity and depth of focus for a spatially filtered imagingsystem as shown in FIG. 11. A white light or broad band LED source isspatially filtered by lens 1101 and pinhole 1111 to provide a wellcollimated beam through lens 1102. If a well collimated source beam isrequired to measure scattering at very low scattering angles (for largeparticles), a laser source might also be used. This collimated beampasses through a cell consisting of two windows, which confine theflowing particle dispersion. Lens 1103 focuses this collimated beamthrough pinhole 1112, which removes most of the scattered light from thebeam. This transmitted beam is transferred to a 2 dimensional detectorarray through lens 1104, which images the center of the sample cell ontothe array. This array will see dark images of each particle on a brightbackground due to the light lost through scattering or absorption by theparticle. A beamsplitter after lens 1103 diverts a portion of the lightto an aperture and lens 1105. The aperture defines a narrow pencil oflight through the cell and a small scattering volume, lowering theprobability of coincidence counts for detectors 1113 and 1114, which arenear to the focal plane of lens 1105. The aperture is optimally placedin the optical plane which is conjugate to the center of the samplecell, through lens 1103. Conjugate planes are a pair of image and objectplanes of an optical system. Detectors 1113 and 1114 are nominallyplaced in the optical plane which is conjugate to the optical source,through lenses 1101, 1102, 1103 and 1105. Detectors 1113 and 1114measure scattered light at two angles, which are nominally below 3degrees for larger particles but which can cover any angular rangeappropriate for the size range of the particle detector. Also more thantwo detectors could be used to increase the size range for this portionof the particle detection system. These detectors could also be annularring detectors (similar configuration to mask 1250 in FIG. 12 and mask8750 in FIG. 86) centered on the optical axis to reduce sensitivity toparticle shape, by equally measuring all scattering planes. For example,detector 1113 could measure a scattering angular region around 1 degree;and detector 1114 could measure around 3 degrees. By combining theparticle scattering pulse signals from these detectors, by ratio orpolynomial, a relatively monotonic function of particle size is createdwithout strong Mie resonances (due to the white light source and signalratio). Detectors 1113 and 1114 count and size particles in much thesame way as the system in FIG. 1. The concept is to use two angles toremove the variations in scattering intensity due to particles passingthrough different portions of the incident beam and to reduce calculatedsize sensitivity to particle and dispersant composition. Particles ofsize between approximately 1 and 10 microns could be handled bydetectors 1113 and 1114 of FIG. 11; and particles above approximately 5microns are handled by the 2-dimensional detector array. The two sizedistributions from these two measurements are combined with blending inthe overlap region between 5 and 10 microns.

The 2-dimensional detector array is imaged into the center of the samplecell with magnification corresponding to approximately 10×10 micron perarray pixel in the sample cell plane. A 10 micron particle will producea single dark pixel if it is centered on one pixel or otherwisepartially darkened adjacent pixels. By summing the total light lost inthese adjacent pixels, the total light absorbed or scattered outside ofpinhole 1112 for each single particle in the view of the array isdetermined. The particle concentration is limited to prevent coincidencecounting in each separate 10×10 micron projection through the samplecell. At low concentrations, any group of contiguous pixels with reducedlight levels will represent a single particle. And the total percentagelight lost by these contiguous pixels determines the particle size. Allpixels below a certain percentage of their non-obscured values areaccepted as particle pixels. All contiguous particle pixels are thencombined as representing one particle. This is accomplished by summingthe pixel values of contiguous pixels and comparing that sum to the sumof those same pixels without the presence of a particle. This works wellfor smaller particles where the total scattered light is well outside ofthe pinhole 1112 aperture, because then the total percentage droprepresents the scattering and absorption extinction of the particle. Forlarger particles, a larger portion of the scattered light will passthrough pinhole 1112 and cause a deviation which will not agree with thetotal theoretical scattering extinction. This scatter leakage can becorrected for in the theoretical model by calculating the actualpercentage loss for larger particles by integrating the actual scatteredlight outside of the pinhole. Alternatively, the particle can be sizeddirectly by counting (and summing the total area of) contiguous pixels,because for the larger particles the detector array pixel size may beless than 0.1% of the total crossectional area of the particle and sothe particle can be sized directly from image dimensions or the totalimage area. The accuracy of this calculation is improved by addingpartial pixels at the edge of the particle image based upon theirattenuation as a fraction of the attenuation of nearby interior pixels.Hence if a pixel in the interior of the image is attenuated by 10% andan edge pixel is attenuated by 4%, that edge pixel should count as 40%of its actual area when added to the sum of all contiguous attenuatedpixels to determine the total crossectional area and size for thatparticle. Otherwise the theoretical loss per particle could be used.

This detector array system has an enormous particle size dynamic range.The particle will remove approximately the light captured by twice itscrossectional area. So a 2 micron particle will reduce the total lightflux on a 10×10 micron pixel by 8 percent. But the entire array of1000×1000 pixels can cover a crossection of 10×10 millimeters. So thesize range can cover 2 microns to 10000 microns. The size dynamic rangeis almost 4 orders of magnitude. The smallest particles are detected bytheir total light scattering and absorption. For very large particles,the angular extent of the scattering pattern may fall within theaperture of pinhole 1112. Then the summed light from all the contiguouspixels may not indicate accurate size. For the larger particles, theactual imaged size is determined by counting contiguous pixels. Pixelsat the outer boundary are counted as partial pixels based upon theamount of light lost as a fraction of the amount lost from pixels in theinterior of the contiguous set. The light loss in each pixel isdetermined by storing the light value for each pixel without particlesin the sample cell and subtracting the particle present values thesestored values. The source intensity can also be monitored to normalizeeach pixel measurement for light source intensity fluctuations.

In order to avoid smeared images, the detector array must integrate thecurrent from each pixel over a short time to reduce the distancetraveled by the particle dispersion flow during the exposure. This mayalso be accomplished by pulsing the light source to reduce the exposuretime. Smearing in the image can be corrected for using deconvolutiontechniques. But the scattering extinction measurements will be accurateas long as each contiguous pixel group does not smear into anothercontiguous pixel group. Add up all of contiguous pixel signals (from thesmeared image of the particle) after presence of the particle todetermine the particle scattering attenuation and size. If the particleimage is smaller than one pixel, then the attenuation of that pixel isthe scattering extinction for that particle. Essentially, you aremeasuring nearly the total amount of light scattered or absorbed by theparticle during the exposure. Using this total lost optical flux dividedby the incident intensity provides the scattering crossection for theparticle, even if the particle is not resolved by the optical system orif that loss is distributed over more pixels than expected from perfectimaging of the particle. This is the power of this technique. The sizeaccuracy is not limited by the image resolution. A 10 mm by 10 mmdetector array, with 10×10 micron pixels, can measure particle diametersfrom a few microns up to 10 mm, with thousands of particles in thesource beam at one time. The 10 mm particles will be sized directly byadding up pixels and multiplying the interior pixels by 1 and the edgepixels by their fractional attenuation and adding all of the pixels upto get the total crossectional area and size. A 5 micron particle,centered on one 10×10 micron pixel, will attenuate that pixel by 50%(the total scattering extinction crossection is approximately twice theactual particle area, outside of the Mie resonance region). In bothcases the particles are easily measured. You are adding up all of thesignal differences (signal without particle—signal with particle) ofcontiguous changed pixels to get the total light lost due the particle.Pinhole 1112 blocks all of the light scattered outside of the angularrange of the pinhole 1112, whose maximum scattering angle is equal tothe inverse tangent of the pinhole 1112 radius divided by the focallength of lens 1103. So the signal difference (signal withoutparticle—signal with particle) is the amount of light scattered by theparticle at scattering angles above this maximum angle of the pinhole,including any light absorbed by the particle. The particle size isdetermined using scattering theory and the ratio of signal change(signal without particle—signal with particle) to the signal without aparticle.

Image smearing could also be reduced by using pulsed flow. The particlesample flow would stop during the period when the light source is pulsedor when the detector array is integrating. Then a flow pulse would pushthe next slug of sample into the detector array field of view before thenext signal collection period. The sample would be approximatelystationary during the signal collection on the detector array. Thispulsing could be accomplished by pressurizing the particle dispersionchamber and using a pulsed valve to leave short segments of the sampledispersion through the source beam interaction volume.

The nearly parallel window cell could also be replaced by a wedge shapedcell which would control the particle count in different size regions,as discussed above (see FIG. 9 a).

Non-spherical particles present another problem for single particlesizing: non-symmetrical scattering patterns. Assume that the incidentlight beam is propagating along the Z direction and the XY plane isperpendicular to the Z direction, with origin at the particle. The XZplane is the center scattering plane of the group of scattering planeswhich are intercepted by detectors 110, 111, 112, and 113. Each detectorsubtends a certain range of scattering angles, both parallel andperpendicular to the center scattering plane. For spherical particles,the scattering pattern is symmetrical about the Z axis and thescattering function could be described in cylindrical coordinates as afunction of Z and of radius R from the Z axis, at some distance Z0 fromthe scattering particle. However, for non-spherical particles thescattering pattern is not symmetrical about the Z axis at Z0. The2-dimensional array in FIG. 11 measures approximately the total lightlost to scattering or absorption at all scattering angles, in allscattering planes. Hence it will produce particle size estimates whichare related to the total crossectional area of the particle, for bothspherical and non-spherical particles, without sensitivity to particleorientation. But detectors 110, 111, 112, and 113 in FIG. 1, andcorresponding detectors in FIG. 3 or 11 measure the scattering only overscattering planes close to the XZ plane (or a limited range ofscattering planes). If the pattern is not symmetrical, the particle sizeestimate will depend upon the orientation of the particle. So a group ofparticles with identical crossectional areas, but random orientations,would be reported over a wide range of particle crossectional area andsize. This particle size distribution width could be corrected bydeconvolution of the number vs. size distribution, as described by thematrix equation shown previously, where matrix M would describe thebroadening of a count distribution from a group of particles, each withthe same particle volume, but with all possible orientations. But thetheoretical model would change with the particle shape. Another way toreduce spread is to use two sets of detector systems, one centered onthe scattering plane which is +45 degrees with respect to the XZ planeand the other at 45 degrees from that plane, to sample two perpendicularparticle orientations and maintain the optimum orientation forheterodyne detection. The average of the size distributions from thesetwo systems would reduce the spread of the distribution. Another moreeffective method is to collect all of the scattered planes at a certainscattering angle, using the system shown in FIG. 12. A light source isfocused into the sample dispersion. This focused spot is imaged onto apinhole which removes unwanted background light. The light passed by thepinhole contains the incident light beam and the scattered light fromthe particles. This light is collected by lens 1203 which projects thelight onto two masks, using a beamsplitter. Each mask contains anannular aperture which defines the range of scattering angle accepted bythe collection optics. Lens 1204 collects high angle scattered lightpassing through mask 1250 and focuses it onto detector 1210. Likewisethe low angle scatter is measured by mask 1251, lens 1205 and detector1211.

FIG. 12 shows the annular aperture for mask 1250, defining equalscattering collection in all the scattering planes. The ratio of signalsfrom detector 1210 and 1211 would precisely determine the average radiusof a non-spherical particle, without size broadening of the systemresponse due to random particle orientation. The beam splitter and dualmask concept could also be applied to the system in FIG. 11. Lens 1105and detectors 1113 and 1114 (all of FIG. 11) would be replaced by lens1203, the beam splitter, the dual mask system, and detectors 1210 and1211 (all of FIG. 12), with the masks in the same optical plane asdetectors 1210 and 1211. Alternatively, lens 1105 and detectors 1113 and1114 (all of FIG. 11) would be replaced by the pinhole, lens 1203, thebeam splitter, the dual mask system, and detectors 1210 and 1211 (all ofFIG. 12), with the pinhole in the image plane of the particles throughlens 1103 of FIG. 11. Masks 1250 and 1251 act as angular filters whichonly pass scattered light in a certain range of scattering angles. The2-dimensional array in FIG. 11 is already insensitive to particleorientation and needs no modification.

The particle concentration must be optimized to provide the largestcount levels while still insuring single particle counting. Theconcentration may be optimized by computer control of particle injectioninto the flow loop which contains the sample cell, as shown in FIG. 13.Concentrated sample is introduced into flow loop 1302 through samplevessel 1312. The sample vessel may also contain a stirring means formaintaining a homogenous dispersion in the vessel. Pump 1320 pumps thedispersion around the loop to provide a homogenous dispersion in theloop and to prevent loss of larger particles through settling. A secondflow system, flow loop 1301, is attached to flow loop 1302 through acomputer controlled valve with minimal dead space. The computer opensthe valve for a predetermined period to inject a small volume ofconcentrated dispersion into loop 1301. The optical system counts theparticles and determines the probability of coincidence counting basedupon Poisson statistics of the counting process. The computer thencalculates the amount of additional particles needed to optimize theconcentration and meters out another injection of concentrated sampleinto loop 1301, through the valve. Actually, both the concentration andpump speed for loop 1301 may be controlled by computer to optimizecounting statistics. When the particle concentration is low, higher pumpspeed will maintain a sufficient particle count rate for good countstatistics. The optimum concentration may be different for differentdetectors and detection systems. Therefore the computer valve may adjustthe concentration to various levels in succession. At each concentrationlevel, data is taken with the appropriate detector(s) for thatconcentration level or detector array for a sufficient period and flowrate to accumulate enough counts to reduce the count uncertainty (due toPoisson statistics) to an acceptable level.

Another consideration for FIG. 6 a is the determination of signalbaseline. The baseline for the scattered signals must be determined foreach detector. Digitized values, measured before and after the scatteredsignal pulse, determine the signal baseline to be subtracted from thepulse signal, by interpolation of those values through the pulse region.These regions before and after each detector pulse should be chosen tobe before and after the widest pulse of the group (in some rare cases,the pulse with the largest amplitude should be used if the signals arelost in noise). Then the baseline will certainly be determined fromvalues in a region where no particle scattering has occurred in each ofthe detectors.

The system shown in FIG. 11 can also be modified to look at onlyscattered light over a certain angular region, instead of the totallight removed from the beam by absorption and/or scattering. FIG. 14shows such an optical system where the light source is spatiallyfiltered by lens 1401 and pinhole 1410. Lens 1402 collimates andprojects the source beam through the particle sample, which is imagedonto the 2 dimensional detector array by lens 1403. An annular spatialmask (or spatial filter) is placed in the back focal plane of lens 1403to only pass scattered light over a certain range of scatter angle asdefined by the inner and outer radii of the annular spatial mask, whichis similar to mask 1250 shown in FIG. 12. The very low angle scatteringand incident beam are blocked by central stop of the annular aperture inthe back focal plane of lens 1403. FIG. 14 shows two such annular masksystems which are accessed through a beamsplitter. The detector arraysare in the image plane of the particles. Hence the detector array 1420sees an image of the particles, and the sum of the contiguous pixelsassociated with each particle's image is equal to the scattered lightfrom that particle over the angular range defined by the aperture (orspatial mask) in the back focal plane of lens 1403. A beam splittersplits off a portion of the light to a second annular spatial mask (inthe back focal plane of lens 1403) and detector array 1421. The angularranges of the two annular spatial filters are chosen to producescattered values which are combined by an algorithm to determine thesize of each particle. The sum of signals from contiguous pixels whichview the same particle are analyzed to produce the particle size. Onesuch algorithm would be a ratio of the corresponding sums (the sum ofcontiguous pixels from the image of each particle) from the sameparticle detected by both arrays. The key advantage is that when theparticle size is too small to size accurately by dimensionalmeasurements on the image (resolution is limited by pixel size) then thetotal scattered light from each particle may be used to determine thesize. And if the total scattered light is sensitive to particlecomposition, then the ratio of the two scattering signals can be used todetermine the particle size more accurately. In FIG. 14, scattered lightis only present when a particle is present. In FIG. 11 the particleimage creates a decrease in light, from a bright background level, onthe 2-Dimensional array in the corresponding pixels, while in the systemof FIG. 14 the particle image creates an increase from a dark backgroundlevel. If the particle is smaller than a single pixel, then the amountof scattered light measured by that pixel will indicate the total lightscattered from that particle in the angular range defined by the focalplane aperture, providing that particle's size. If more than one pixelis associated with a particle, those pixel values are summed together toobtain the scattered signal from that particle in a similar fashion asdescribed before for FIG. 11. The only difference is that the increasein pixel signals, relative to the signal without particles, are summedto produce the total light scattered from that particle in the angularrange of the annular aperture in FIG. 14. In FIG. 11, the decrease inpixel signals, relative to the signal without particles, are summed toproduce the light lost due to scattering outside of pinhole 1112 orabsorption by that particle. Signal to background should be better forFIG. 14, but with higher sensitivity to particle composition andposition in the sample cell. The depth of focus and signal to noiseshould be better for FIG. 11 than for FIG. 14, because the pixel valuesdrop by the total light scattered and absorbed by the particle in FIG.14 as opposed to the light increasing by only the amount scatteredthrough a narrow range of scattering angles defined by the aperture. Aswith all other systems described in this disclosure, these ideas can beextended to more than two detector arrays or more than two scatteringangles, simply by adding more annular spatial masks and detectors byusing beamsplitters. Also the 2-dimensional array optics in FIG. 11could be combined, by beamsplitters, with those in FIG. 14 to providetotal scatter information (both angular scatter and total light loss dueto scatter and absorption) for determining size and to provide theunscattered intensity for each pixel to normalize the pixel scatter dataof FIG. 14 detectors for the incident light intensity which may varyacross the beam. In this way, each pixel in the detector array creates asmall independent interaction volume, providing individual detection ofa very small particle contained in that interaction volume, with lowcoincidence probability. But yet contiguous pixels can be combined tomeasure particles of sizes approaching the dimensions of the entiredetector array's image in the sample cell. The size dynamic range isenormous. FIG. 14 could also be used with a source beam which is focusedinto the sample cell to reduce the interaction volume and increase thebeam intensity and scattered signal. In this case the center portion ofthe annular mask must be increased in size to block the diverging lightfrom the source so that each detector array only sees scattered light.

The optical source used with the detector arrays in FIGS. 11 and 14could be a pulsed broad band source such as a xenon flash lamp whichproduces broadband light to wash out the Mie resonances, and whichproduces a short light pulse to freeze the motion of particles flowingthrough the cell.

One problem with the techniques described above is coincidence counting.The cell path must be large to pass the largest anticipated particle(except for the wedge cell shown in FIG. 9 a, where the pathlengthchanges across the cell). Hence for these collimated systems, many smallparticles may be in any sample volume seen by a single pixel. Thesecoincidences could possibly be eliminated by measuring at variousparticle concentrations, but in order to count sufficient largeparticles to obtain reasonable count accuracy, the concentration must beraised to a level where more than one small particle is present in thesample cell volume, seen by each pixel. The scattered signals from thesemultiple particles can be separated, to be counted individually, bymeasuring their settling velocities. This is accomplished by the opticalsystem shown in FIG. 15. A light source is collimated and spatiallyfiltered by lenses 1501 and 1502 and pinhole 1520. A modulation transfertarget or mask with a spatially periodic transmission function is placedin the collimated beam to create a sinusoidal (or other periodicfunction) intensity pattern in the collimated beam. This mask could alsobe placed in any plane which is conjugate to the particles, includingthe location shown in FIG. 64. The mask could also be placed in a plane,between lens 1502 and the light source, which is conjugate to theparticles. The mask could also be placed in a plane, between the scattercollection lens (lens 1503 in FIG. 15) and the multi-element detector,which is conjugate to the particles. Examples of the sinusoidal (orother periodic) patterns are shown in FIG. 16. Each line in the patternsrepresents the peak of the sinusoidal transmission function whichoscillates along the particle settling direction but is constant alongthe direction perpendicular to the settling. The mask consists ofmultiple regions with different spatial modulation frequencies. Theprojection of each region into the sample cell is imaged onto a separatedetector by lens 1503. The light from lens 1503 is split into one ormore directions, each having a different annular spatial mask whichdefines a different range of scattering angles. Each image plane foreach spatial mask has multiple detectors, each of which intercept lightfrom only one of mask regions in the sample cell. As a particle settlesthrough the sinusoidal intensity pattern, the scattered light on thedetector is modulated because the scattered light is proportional to thelight intensity incident on the particle and the mask provides aspatially modulated illumination field. When a particle passes through aregion where the spatial modulation wavelength is greater than theparticle size, the scattered light from that particle will attain alarge modulation visibility (the ratio of peak to trough values will belarge). The scattered signal from the largest particles will have lowestmodulation visibility in the high spatial frequency region because theparticle will span over multiple cycles of the spatial modulation.Larger particles settle faster and produce higher frequency detectorsignals, because they have a higher terminal velocity. Therefore, alower spatial modulation frequency can be used with larger particles toincrease modulation visibility while still maintaining high signaloscillation frequency, because the scattering signal frequency is equalto the product of settling velocity and the mask spatial frequency. Thesize range is increased by using multiple regions with different spatialmodulation frequencies, with higher frequencies for smaller slowersettling particles. The area of the higher frequency portions of themask are smaller to reduce the number of particles measured at one timeby each detector, because typically there are much higher small particlecounts per unit volume than for larger particles. FIG. 15 a shows asimilar system with a single pinhole filter. Detector signals will showthe same oscillation characteristics as FIG. 15, but with a large offsetdue to the light transmitted by the pinhole. The power spectrum of thedetector currents for the systems shown in both FIGS. 15 and 15 a willbe similar except that FIG. 15 a will contain a large component at (andnear to) zero frequency. FIG. 17 shows the power spectra from the lowand high angle detector signals in FIG. 15, for the two detectorelements, B1 and B2, which view the same portion, B, of the mask, butpass through different annular filters. Since each particle settles at adifferent velocity, each particle will produce a separate narrow peak atthe same frequency in both of the power spectra of detectors B1 and B2(from signals for scattering angle 1 and scattering angle 2,respectively). This is due to the fact that the detector signal power atany certain frequency, measured by each of the corresponding low andhigh angle detectors, will originate from the same particle or group ofparticles. Since the smaller particles will create a continuum at lowerfrequencies, they can be removed from the spectrum of the largerparticles. The corresponding single peak values from power spectrum ofcurrent from detector B1 at frequency f1 and the power spectrum fromcurrent of detector B2 at frequency f1 for example (from each scatteringangle) can be ratioed (or analyzed by other algorithms) to determine thesize of the particle which created that peak in each spectra. In thisway, multiple particles in the sampling volume can be countedindividually. When particle size is close to the line spacing of themodulation target, the modulation of the scattered light will decreasebecause the signal is the convolution of the particle with themodulation target. However, the amplitude of the scattered signals atboth angles will both decrease by the same percentage so that theirratio will still accurately indicate the size. Any peaks with amplitudesthat are higher than that which would be expected from one particle areexpected to originate from more than one particle. The expectedamplitude for a single particle can be determined from the minimum valueof other peaks in that frequency region for prior digitization sets.These multiple particle peaks can be either corrected for the secondparticle's contribution or eliminated from the particle count. If theparticle density, liquid density and viscosity, are known, eachindividual particle size can also be determined by the frequency of thecorresponding peak, by calculating the corresponding settling velocityand using the Stokes equation for settling to solve for the particlesize.

The signal frequency for each particle signal pulse could also bedetermined individually by either the timing of zero crossings or byusing a phase locked loop, avoiding the power spectrum calculation. Eachparticle pulse will consist of a train of oscillations which aremodulated by the intensity profile through that particular mask region.The oscillation amplitude and frequency provide the scattering amplitudeand settling velocity, respectively, for that particle. The size can bedetermined from the settling velocity, if the particle density and fluidviscosity are known, or the size can be determined from the ratio ofamplitudes from two different scattering angles (or angular ranges), orthe amplitude at one scattering angle (or angular range) (but withpossible higher sensitivity to particle composition).

The particle density or fluid viscosity can be determined by combinationof the scattering amplitudes and the signal oscillation frequency.

Mask 1602 could be modified to provide different length sections asshown in FIG. 16 a. In this case, each mask section would have aseparate matching detector as shown in FIGS. 15, 15 a, or 64, but thedetectors and mask sections are spaced in the plane perpendicular to theflow. This mask could be used with the wedged sample cell in FIG. 9 a(where the y direction is out of the page) to provide definition ofdiffering sized interaction volumes. The mask determines x and ydimensions and the pathlength of the cell provides the z dimension foreach interaction volume. The cell pathlengths could also be defined bystepped regions instead of a continuous decrease in pathlength acrossthe cell. The signals from different portions of the cell can beseparated by using multiple detectors or based upon signal frequency asdescribed previously for FIG. 16, in either settling or flowing modes.Also the mask in FIG. 16 b provides a continuously variable spatialfrequency across the sample cell, so that particles in each portion ofthe wedged sample cell will produce signals of differing frequency, ineither the flow or settling case. This separation of interaction volumesin the wedged cell could also be provided by the detector array, shownin FIG. 16 c, which defines ever decreasing interaction volumes for eachdetector element. Using the wedged sample cell in FIG. 14, each of thetwo detector arrays in FIG. 14 could be replaced by detector arrays, asshown in FIG. 16 c, to measure two scattering angles for eachinteraction volume defined in the wedged cell. In all cases, the thinend of the wedge or the smallest mask opening is oriented to line upwith the thin portion of the sample cell wedge so as to define everdecreasing interaction volumes in x, y, and z dimensions.

FIG. 18 shows another system for measuring the settling of particles,using crossed laser beams. The laser source is split into two beams by abeamsplitter. Lens 1802 focuses those beams in the particle dispersion.An interference pattern is formed at the intersection of the beams. Asthe particles pass through this pattern, the scattered light, measuredby either detector, is modulated, producing a power spectrum asdescribed above. As described previously, the amplitudes of thecorresponding peaks (at the same frequency) in power spectra of thedetector signals can be used separately, or in ratio, to determine theparticle size.

All slit apertures in this disclosure (for example, slit 114 and slit115 in FIG. 1) can be changed to pinholes or rectangular apertures,whose images at the source beam may be or may not be smaller than thesource beam. Unlike slits, the pinholes or rectangular apertures mayrequire alignment in the both of the mutually perpendicular X and Ydirections, which are both approximately perpendicular to the opticalaxis of the detection system.

FIG. 19 (or FIG. 106) shows more detail of the actual beam shapes inFIG. 1 for the angular ranges specified for detectors 1911 through 1914.The scattering angle range for each detector is controlled by thedetector size or by an aperture on front of a larger detector. FIG. 20shows the detail of the intersection of the each detector field of viewwith source beam.

If the signal to noise is sufficient for non-coherent detection with anydetector in FIG. 1, or in any other variation of FIG. 1 shown in thisdocument, the local oscillator optics for that detector can be removedand non-coherent detection can be used.

The progression of crossectional size, in the interaction volume, fromsmallest to largest is: light source, fields of view from detectors 2003and 2004, and the fields of view from detectors 2001 and 2002, as shownin FIG. 20. The progression could also progress from the smallest tolargest as light source, field of views of detector 2004, detector 2003,detector 2002, and detector 2001, respectively. However, this wouldrequire different sized apertures for each detector. This would requirea separate lens and aperture for each detector, but would insure thatany particle passing through the intersection of the source beam and thedetector 2004 field of view, will be seen by all of the other detectorsduring the entire pulse period from detector 2004. Then if all of thedetector signal ratios are measured during a period near to the peak ofthe detector 2004 signal (after the envelope detector), valid scatteringratios will be recorded for all of the detectors.

The particles being measured by system in FIG. 19 are all much smallerthan the crossection of the source beam. Therefore particles ofdifferent sizes produce the same count-vs.-parameter distribution forthe following parameters:

-   1) scattered light amplitude normalized to the maximum scattered    light amplitude measured over all the particles of the same size at    that scattering angle.-   2) Pulse width at certain fraction of pulse peak level-   3) delay between pulses from two different detectors-   4) correlation between pulses from two different detectors

Any of these parameters can be used to define a threshold for countingparticles as shown in FIGS. 10 and 10 a, by replacing the S(a2) axiswith one of the parameters from above. If the particle count is large,the statistics of the above parameters will be stationary for allparticle sizes. Then the strategy outlined for FIG. 10 can be used toproperly threshold particles of all sizes in an equivalent manner, byrejecting the same percentage of particles in each size bin in thecount-vs.-size distribution. The 3 dimensional surface which correspondsto the one in FIG. 10, can be interpolated or fit to a surface functionin order to determine the rejection threshold. Based upon the functionor interpolated values, a rejection criteria can be determined whicheliminates the particles with poor signal to noise and also removes thesame percentage of particles from each size range so as to maintain atrue particle size distribution. The rejection threshold is chosen tomaintain a sufficiently high signal-to-noise for any particles which areaccepted into the total count distribution. In fact, this process willcomputationally define an interaction volume for the source beam and alldetector fields of view, for all particle sizes being detected, whereall scattering signals have sufficient signal-to-noise to produceaccurate sizes based upon their amplitudes, ratios of amplitudes, orother multi-parameter functions of scattering amplitudes. This selectionprocess is required to reduce the effects of the tails in the intensitydistribution of the source and the spatial response tails at the edgesof the detector fields of view, where they intersect the source beam. Ifthese tails are sharpened (or cut off) by spatial filtering the sourceor by using slits, pinholes, or other apertures with low aberrationoptics for the detectors, the errors due to these tails are furtherreduced, as shown in FIG. 10 a. Also diffractive optics can be used toproduce a “flat top” intensity distribution from a Gaussian laserintensity profile. Then the corresponding flat top shape should be usedto produce the functions in FIGS. 10 and 10 a. This would improve theaccuracy of the particle rejection threshold and the resulting particlecount distribution. In any event, there is always some parameter whichis statistically well described by the millions of particles which aredetected. And by eliminating particles from the count based upon thisparameter, you can define a group of particles which are sorted by thesame criteria at all particle sizes, thereby creating an accurate sizedistribution, while removing count events which have poor signal tonoise.

In the sample cell with flat windows, many of the incident source beamsand scattered light rays are at high angles of incidence on the samplecell windows. The interior surface of the window is in contact with aliquid which reduces the Fresnel reflection at that surface. However,the exterior surface is in air which can cause an enormous Fresnelreflection at these high incident angles. This reflection can be reducedby anti-reflection coating the exterior surface, but with high cost. Abetter solution is to attach prisms (see FIG. 21) to the exteriorsurface with index matching optical adhesive. The prism surfaces presentlow angles of incidence for the source beams and the scattered light.Even simple antireflection coatings on the external prism surfaces willreduce the Fresnel reflections to negligible levels. A sphericalplano-convex lens, with center of curvature near to the center of thecell could also be used instead of each prism, with plano side attachedto the window.

Another configuration for the sample cell is a cylindrical tube. Theparticle dispersion would flow through the tube and the scattering planewould be nearly perpendicular to the tube axis and flow direction. Inthis case, the beam focus and detector fields of view would remaincoincident in the scattering plane for various dispersant refractiveindices and only inexpensive antireflection coatings are needed.However, since the flow is perpendicular to the scattering plane, theheterodyne oscillations cannot be produced by the particle motion. Theoptical phase modulation mirror in the local oscillator arm (called“mirror”) in FIGS. 1 and 19 (and other figures) could be oscillated toprovide a heterodyne signal on detectors 112 and 113 as describedbefore. This could also be accomplished with other types of opticalphase modulators (electro-optic and acousto-optic) or frequency shifters(acousto-optic).

Any of the measurement techniques described can be used individually orin combination to cover various particle size ranges. Examples ofpossible combinations are listed below:

For particle diameter 0.05-0.5 microns use FIG. 19 with detectors 1913and 1914 at 30 and 80 degrees, respectively.

Use heterodyne detection (if needed). Take ratio of the detectorsignals.

For particle diameter 0.4-1.2 microns use FIG. 19 with detectors 1911and 1912 at 10 and 20 degrees, respectively.

Use heterodyne detection (if needed). Take ratio of the detectorsignals.

All 4 signals can also be used together for the range 0.05 to 1.2microns, using a 4 parameter function or lookup tables.

Many choices for scattering angles will provide high sensitivity to sizein certain size ranges. These include the following examples of ratiosof signals for various particle size ranges: 75 degree/10 degree for0.05 to 0.5 micron particles, 10 degree/1 degree for 2 to 15 micronparticles, 2 degree/1 degree for 0.5 to 4 micron particles, 10 degree/2degree for 1 to 5 micron particles, 25 degree/15 degree for 0.4 to 1.4micron particles, 10 to 20 degrees/5 to 8 degrees for 0.05 to 1.6 micronparticles, 25 to 50 degrees/5 to 8 degrees for 0.3 to 0.7 micronparticles. Any single angle specification assumes that scattered lightis collected in some angular range which is centered on that angle anddoes not have extensive overlap with the angular range of the otherangle in the ratio. These angle pairs could also be used separately todetermine particle size, based upon absolute amplitude (instead ofratio) and using look up tables, simultaneous equations, or the2-dimensional analysis shown later (see FIG. 26 for example).

Use the detector with the smallest interaction volume to trigger datacollection.

These angles are only representative of general ranges. Almost anycombination of angles will provide sensitivity to size over a certainsize range. But some combinations will provide greater size sensitivityand larger size range. For example, instead of 10, 20, 30, 80 degreeangles, any group of angles with one widely spaced pair belowapproximately 30 degrees and another widely spaced pair aboveapproximately 30 degrees would work. Each detector sees an angular rangecentered about the average angle specified above. But each detectorangular range could be somewhat less than the angular spacing betweenmembers of a detector pair. In some cases, without optical phasemodulation, the angular ranges of each heterodyne detector should belimited to prevent heterodyne spectral broadening as described later(see FIG. 91). The particle size distribution, below 2 microns, fromthis system is combined with the size distribution above 1 micron asdetermined from various other systems described in this disclosure,including the following systems:

For particle diameter 1-10 microns use detectors 1113 and 1114, in FIG.11 or 1420 and 1421 in FIG. 14, at approximately 1 degree and 3 degrees,respectively. Use white light or LED source. Use ratio of detectorsignals to determine individual particle size.

For particle diameter greater than 1 microns, use the 2 dimensionalarray in FIG. 11 with a pulsed white light source (such as a pulsedxenon source) to freeze the motion of the flowing particles. The twodimensional array could also be used alone to measure greater than 1micron, without detectors 1113 and 1114. The system in FIG. 14 couldalso measure particles greater than 1 micron in diameter, with one(absolute) or both (ratio) detector arrays.

Another configuration is to use the scattering flux ratio of scatteringat 4 degrees and 1 degree, in white light, for 0.5 to 3.5 microns. Anduse absolute flux at 1 degree (white light, same system) for 3 to 15microns. And use the 2 dimensional array in FIG. 11 or 14 for particlesabove 10 microns. As noted above, each array in FIG. 14 can separatelybe used to size particles by measuring the absolute scattered light fromeach particle, or light lost due to the particle, over one angularrange. However, the system size response will be more composition(particle and dispersant refractive indices) dependent using data from asingle array than the ratio of the corresponding measurements from botharrays.

In all of these systems, the white light source can be replaced by alaser. However, the particle size response will become more sensitive toparticle and dispersant composition. And also the response vs. size maynot be monotonic due to interference effects between the particlescattered light and light transmitted by the particle (Mie resonances),producing large size errors. If lasers or LEDs are required forcollimation or cost requirements, scattering measurements can be made atmore than one wavelength, using multiple sources, to reduce thecomposition dependence. Particle size of each object would be determinedfrom all of these multi-wavelength measurements by using amulti-parameter function (size=function of multiple parameters), byinterpolation in a lookup table as described above, or by a searchalgorithm. And in all cases the angles are nominal. Many differentcombinations of average angles, and ranges of angles about those averageangles, can be used. Each combination has a different useable particlesize range based upon size sensitivity, composition sensitivity, andmonotonicity. All of these different possible combinations are claimedin this application. Also note that the ratio of S(a1)/S(a2) in FIG. 10can be replaced by any parameter or function of parameters which havenearly exclusive sensitivity to particle size, with low sensitivity toincident intensity on the particle. This may include functions ofscattering measurements at more than 2 angles.

These cases are only examples of combinations of systems, described inthis application, which could be combined to provide a larger particlesize range. Many other combinations are possible and claimed by thisinventor.

One problem associated with measuring large particles is settling. Thesystem flow should be maintained at a sufficiently high level such thatthe larger particles remain entrained in the dispersant. This isrequired so that the scattered light measurements represent the originalsize distribution of the sample. For dense large particles,impracticable flow speeds may be required. This problem may be avoidedby measuring all of the particles in one single pass, so that the totalsample is counted even though the larger particles may pass through thelight beam as a group (due to their higher settling velocities) beforethe smaller particles.

A small open tank is placed above the sample cell region, connected tothe cell through a tube. The tube contains a valve which can be shutduring introduction of the particle sample into the tank to prevent thesample from passing through the cell until the appropriate time. Theliquid in the tank is continuously stirred during the introduction ofsample to maximize the homogeneity in the tank. A light beam may bepassed through the mixing vessel via two windows to measure scatteredlight or extinction to assist in determining the optimum amount ofsample to add to obtain the largest counts without a high coincidencecount level. The optical detectors are turned on and the valve is openedto allow the particle mixture to pass through the cell withgravitational force. This can also be accomplished by a valve below thesample cell or by tilting the tank up to allow the mixture to flow overa lip and down through the cell, as shown in FIG. 22. The light beamcould be wider than the width of the flow stream through the cell sothat all of the particles passing through the cell are counted. Singleparticle counting is assured by only introducing a sufficiently smallamount of sample into the tank. Since all of the larger particles arecounted in one pass, the count distribution is independent of the sampleinhomogeneity. After the entire sample has passed through the cell, theconventional flow system for ensemble scattering measurements is thenturned on to circulate the sample through the cell. Ensemble scatteringmeasurements are measurements of scattered light from groups ofparticles. This flow rate must only be sufficient to suspend theparticles which were too small, or too numerous, to be individuallycounted during the single pass. During this flow period, settling of thelarger particles which have been counted does not matter because theircount distribution (from the single pass) will be combined with thecount-vs.-size distribution of the smaller particles (obtained duringflow) to produce a single volume distribution over the entire sizerange, using the size distribution blending and combination methodsdescribed previously.

The system in FIG. 22 could also be used alone to provide significantcost savings by eliminating the pump and associated hardware. FIG. 22shows the concept for dispersing and measuring the particles in a singlepass through the optical system. The particles and dispersant are mixedcontinuously in a mixing vessel which is connected to the optical systemthrough a flexible tube. The mixing vessel is tilted while being filled,so that no sample enters the optical system. Then once the dispersion iswell mixed, the mixing chamber is sealed with a gas tight cover and themixing vessel is moved into an upright position to allow the dispersionto either fall through the sample cell under gravity (without gas tightcover) or to be pushed through the cell using gas pressure. If gaspressure is not used, the flexible tube could be eliminated and themixing vessel could pour into a funnel on top of the sample cell.

The systems based upon FIG. 19 and similar systems, where scatteredlight at multiple-angles are measured from a single particle, will havea lower particle size limit due to the lower scattering intensity ofsmall particles and insensitivity of the scattering ratio to particlesize. If the particle refractive index and dispersant refractive indexare known, various scattering theories can be used to calculate thescattering signal ratios and absolute scattering signals vs. particlesize to provide the look up table or function to calculate the size ofeach particle from these signals. Since these refractive index valuesare not always available, the scattering model (the effective refractiveindices) may need to be determined empirically from scattering datameasured in a region where the scattering ratio is independent ofrefractive index, but where the absolute scattering amplitudes aredependent upon refractive index. In this region the signal ratio willdetermine the particle size. And then the absolute scattering signals(relative to the incident source intensity) and this size value can beused to determine the refractive indices by using global searchalgorithms to search for the refractive indices which give the best fitto the particle size and absolute signal values. This process assumesthat the entire particle ensemble is homogeneous in individual particlecomposition (however, a method is proposed for dealing withinhomogeneous samples in FIG. 27 a). This method can be used for anyparticle, which shows a ratio in the size sensitive region of theresponse, and this method can be used to determine the effectiverefractive index of the particle by using the ratio and the absolutevalues of the scattering signals, because these are unique for particleand dispersant refractive index. The optical model for this effectiverefractive index could then be used to extend the size response range,of any set of detectors, to a size range outside of the ratio determinedsize region (where the scattering signal ratio is sensitive to size andthe ratio cannot be used). This process can extend the size to bothsmaller and larger particles by using the absolute scattering intensityin regions where the scattering signal ratio no longer works.Theoretically, very small particles are Rayleigh scatterers, where theshape of the angular scattering distribution is not size dependent.However for very small particles, the peak of the scattering intensitydistribution scales as the 6^(th) power of the particle diameter and theheterodyne signal scales as the 3^(rd) power of the diameter. So as theparticle size decreases, the ratio of the intensity at two anglesbecomes constant, but the actual intensities continue to drop as theparticle size decreases. So when the intensity ratio approaches thisconstant, the particle size algorithm should use absolute scatteringintensity to determine the size. The absolute scattered intensity isproportional to a constant (which is a function of scattering angle,particle and dispersant refractive indices, and light wavelength)divided by particle diameter to the 6^(th) power (3^(rd) power for theheterodyne signal). This constant is determined from the absolutescattered intensities of particles, in the distribution, whose intensityratios still provide accurate particle size. Also the functional formfor the absolute intensities can be calculated using various scatteringtheories (Mie theory for example). This process can also be used toextend the useful range to larger particles. As the particle becomeslarger, the scattering signal ratio from the detector pair will becomemore dependent upon the refractive index of the particle. The absoluteintensity data from particles, in the region where the ratio isindependent of particle composition, can be used to determine theeffective composition of the particles and determine which theoreticalscattering model to use for absolute scattering intensity from particlesoutside of that size region. Then the larger particles are measuredusing this model and the absolute values from each scattering detector,instead of the ratio of scattering signals. Absolute intensity data fromparticles, in the region where the ratio is independent of particlecomposition is preferred, but absolute scatter data from multiplescattering angular ranges in any size region can be used to determinethe particle and dispersant refractive indices by using the globalsearch algorithms described elsewhere in this application. Thescattering values depend more strongly on the ratio of particlerefractive index to dispersant refractive index, than their absolutevalues. So in many cases, only the refractive index ratio must bedetermined by this search algorithm.

One other remaining problem with absolute scattering intensitymeasurements is the sensitivity of pulse intensity to the position wherethe particle passes through the beam. Measuring the distribution ofpulse amplitudes from a nearly mono-sized calibration particledispersion (with a low coefficient of variation for the sizedistribution) provides the response of the counter for a group ofparticles of nearly identical size. This count distribution, which isthe same for any particle whose size is much smaller than the light beamcrossection, provides the impulse response for a deconvolution procedurelike the one described previously. The scattering pulses can be selectedbased upon their pulse length by only choosing pulses with intensitynormalized lengths above some threshold or by using the various pulseselection criteria listed below. This selection process will help tonarrow the impulse response and improve the accuracy of thedeconvolution. This process is also improved by controlling theintensity profile to be nearly “flat top” as described previously.

The scattered signal from any particle is proportional to the intensityof the light incident on the particle. Hence as the particle passesthrough different portions of the incident light beam, each scatteredsignal will vary, but the ratio of any two signals (at two differentscattering angles) will theoretically be constant as long as the fieldof view of each detector can see the particle at the same time. This canbe insured by eliminating the signals from long intensity tails, of theGaussian intensity profile of the laser beam, which may not be seen byall detectors. This is accomplished by placing an aperture, which cutsoff the tails (which may be Gaussian) of the incident light intensitydistribution, in an image plane which is conjugate to the interactionvolume. This aperture will produce a tail-less illumination distributionin the interaction volume, providing a narrower size range response tomono-sized particle samples (the impulse response). In the case of anelliptical Gaussian from a laser diode, the aperture size could bechosen to cut the distribution at approximately the 50% points in boththe x and y directions (which are perpendicular to the propagationdirection). Such an aperture would cause higher angle diffractive lobesin the far field of the interaction volume, which could cause largescatter background for low scattering angle detectors. Since thisaperture should only be used for measurements at high scattering angleswhere the background scatter can be avoided, the low angle detector setand high angle detector set may need to view separate light beams. Theapertured beam size should be much larger than the particles which arebeing measured in that beam. Hence, to cover a large size range,apertured beams of various sizes could be implemented. The particle sizedistributions from these independent systems (different source beams ordifferent detector groups) could be combined to produce one continuousdistribution. These apertures could also have soft edges to apodize thebeam, using known methods to flatten the beam intensity profile whilecontrolling the scattering by the aperture. This could also beaccomplished by using diffractive optics for producing flat topdistributions from Gaussian beam profiles as mentioned earlier. Alsoapertures can be oriented to only cut into the beam in the appropriatedirection such that the diffracted light from that beam obstruction willbe in the plane other than the scattering plane of the detectors. Thisis accomplished by orienting the aperture edges so that they are notperpendicular to the scattering plane. The aperture edges which cut intothe beam at higher levels of the intensity profile should be nearlyparallel to the scattering plane to avoid high scattering background.

The apertured beams will help to reduce the size width of the systemresponse to a mono-sized particle ensemble, because the intensityvariation of the portion of the beam which is passed by the aperture isreduced. Other analysis methods are also effective to reduce themono-sized response width for absolute scattering and scattering ratiomeasurements. Methods which accept only scattering signal pulses, orportion of pulses, which meet certain criteria can be very effective innarrowing the size width of the system response to mono-sized particles.Some examples of these acceptance criteria are listed below. Any ofthese criteria can be used to determine which peaks or which portion ofthe peaks to be used for either using the scattering signal ratios orabsolute values to determine the particle size.

-   1. Choose only the time portion of both pulses where the pulse from    the detector which sees the smaller interaction volume, or has the    shorter duration, is above some threshold. The threshold could be    chosen to be just above the noise level or at some higher level to    eliminate any possibility of measuring one signal while the second    signal is not present. Then either take the ratio of the signals (or    ratio the peaks of the signals with peak detector) over that time    portion or the ratio of the integrals of the signals over that time    portion. The absolute integrals or peak values during this time    portion could also be used to determine size, as described before.-   2. Only accept pulses where the separation (or time delay between    peaks or rising edges) between pulses from the multiple detectors is    below some limit-   3. Only accept pulses where the width of a normalized pulse or width    of a pulse at some threshold level is within a certain range as    determined by the shortest and longest particle travel paths through    the accepted portion of the interaction volume.-   4. Only accept the portion of the pulses where the running product    S1.*S2 (a vector containing the products of S1 and S2 for every    point during the pulses) of the two signals is above some limit.    Then either take the ratio of the signals over that portion or the    ratio of the integrals of the signals over that portion.-   5. Only use the portion of pulses where    sum(S1.*S2)/(sum(S1)*sum(S2)) is greater than some limit    (sum(x)=summation of the data points in vector x)-   6. Use only the portion of the pulses where (S1.*S2)/(S1+S2) is    greater than some limit-   7. integrate each pulse and normalize each integral to the pulse    length or sample length-   8. Use only the portion of the pulses where the value of S1*S2 is be    greater than some fraction of the peak value of the running product    S1.*S2-   9. Integrate both signals S1 and S2 only while the signal from the    smaller interaction volume is above a threshold or while any of the    above criteria are met.-   10. fit a function to the selected portion (based upon various    criteria described above) of each pulse. The fitting function form    can be measured from the signal of a particle passing through the    center of the beam or can be based upon the beam intensity profile-   11. When both S1 and S2 have risen above some threshold, start    integrating (or sample the integrators from) both signals. If the    integrators for S1 and S2 are integrating continually (with resets    whenever they approach saturation) then these integrators could be    sampled at various times and the differences would be used to    determine the integrals in between two sample times. Otherwise the    integrators could be started and stopped over the period of    interest. These sampled integrals are IT10 and IT20 for S1 and S2    respectively, when each of them rises above the threshold. When the    first signal to drop falls back down below the threshold, sample the    integrator on each of S1 and S2 (integrals IT1 a and IT2 a). When    the second signal (signal number *) to drop falls below the    threshold, sample the integral IT*b for that signal. Use the ratio    of the integral differences, (IT1 a−IT10)/(IT2 a−IT20), during the    period when both signals are above the threshold to determine size.    Accept and count only pulses where a second ratio    (IT*a−IT*0)/(IT*b−IT*0) is above some limit. This second ratio    indicates the fraction of the longer pulse which occurs during the    shorter pulse. As the particle passes through the light beam further    away from the center of the interaction volume, this ratio will    decrease. Only particles which pass through the beam close to the    center of the interaction volume will be chosen by only accepting    pulses where the shorter pulse length is a large fraction of the    longer pulse length. These pulse lengths could also be determined by    measuring the difference in the length of time between the above    trigger points for each pulse. Pulses with a shorter difference in    time length are accepted into the count by ratioing their integrals    during the period when both of them are above the threshold.

These criteria can be easily implemented by digitizing S1 and S2 andthen doing the above comparisons digitally. However, full waveformdigitization and digital analysis of 1 million particles may require toomuch time. FIGS. 23 a and 23 b show configurations for implementing someof these criteria using analog circuits. The signal digitization andcomputational load is greatly reduced by using analog equivalents topreprocess data before digitization. This concept is particularlyeffective when the thresholding or comparative functions, of thecriteria described above, are replaced by analog equivalents; but theactual signal analysis used for size determination is done digitally toavoid the poorer linearity and accuracy of the analog equivalents. Anexample of this is shown in FIG. 23 b, where both integrator outputs(one integration per signal pulse) are separately digitized by the A/Dconverters to do the amplitude or signal ratio calculations digitallyinstead of using analog ratio circuits; but the criteria relatedfunctions, analog multiply and comparator, are done analog to reduce thedigitization load. This overall concept of using analog circuitryspecifically for only the criteria related functions to reduce thedigitization load is claimed by this disclosure, along with applicationsto other systems.

All of these variations will not be perfect. Many of them rely uponapproximations which can lead to variation in calculated size for aparticle that passes through different portions of the beam. Theimportant advantage is that the broadening of the mono-sized particleresponse is the same for all size particles which are much smaller thanthe source beam. Therefore this broadened response, which is calculatedby measuring the count distribution from a mono-sized distribution or bytheoretical modeling, can be used as the impulse response to deconvolvethe count distribution of any size distribution.

The intensity ratio is sensitive to size and mildly sensitive toparticle and dispersant refractive index. Size accuracy is improved byusing scattering theory (such as Mie theory for spherical particles),for the actual refractive index values, to calculate the scatteringratio vs. particle diameter function. However, sometimes theserefractive indices are not easily determined. Three scattering anglescould be measured to generate a function which has reduced sensitivityto refractive index.

D=A1*(S2/S1)+A2*(S2/S1)̂2+A3*(S2/S1)̂3+B1*(S3/S1)+B2*(S3/S1)̂2+B3*(S3/S1)̂3+C1

D=particle diameterA1, A2, A3, B1, B2, B3 are constantsS1=scattering signal at the first scattering angle (over the firstscattering angle range)S2=scattering signal at the second scattering angle (over the secondscattering angle range)S3=scattering signal at the third scattering angle (over the thirdscattering angle range)

Solve the set of equations:

Di=A1*(S2/S1)ij+A2*((S2/S1)ij)̂2+A3*((S2/S1)ij)̂3+B1*(S3/S1)ij+B2*((S3/S1)ij)̂2+B3*((S3/S1)ij)̂3+C1

where

-   -   i=diameter index    -   j=index of refraction index        and        S1 ij=theoretical scattering signal over scattering angular        range #1, for particle diameter D=Di and the jth index of        refraction        S2 ij=theoretical scattering signal over scattering angular        range #2, for particle diameter D=Di and the jth index of        refraction        ( . . . )ij indicates that all the variables inside the        parentheses have index ij.

A set of simultaneous equations are created for various diameters Diusing signal ratios calculated from the appropriate scattering theory(Mie theory or non-spherical scattering theory) for various particle anddispersant refractive indices. These equations are then solved for theconstants A1, A2, A3, B1, B2, B3, C1 and the scattering angles. Ofcourse this process can be extended to more than 3 angles and forpolynomial order greater than 3. These constants and scattering anglesare determined using iterative search or optimization methods torepeatedly adjust these parameters to maximize the sensitivity toparticle size, while lowering the sensitivity to particle and dispersantrefractive indices.

Particles which are two small for single particle counting may bemeasured by stopping the flow and using the heterodyne signal of thescattered light to measure the size distribution from the Brownianmotion of the particles. This Brownian measurement should be done athigher particle concentration, before the particle dispersion isauto-diluted to the lower counting concentration by the system shown inFIG. 13. The particle size distribution is determined by invertingeither the power spectrum or the auto-correlation function of theDoppler broadened scattered light from the moving particles, using knownmethods. The particle size distribution from Brownian motion can also beused to determine the effective particle/dispersant refractive index(scattering model) by measuring the hydrodynamic size of a particlealong with the scattering signal amplitudes. The scattering model can bedetermined from the scattering intensity at each angle, and the truesize for a representative single particle or a group of particles. Thetrue size can be determined from the power spectrum or autocorrelationfunction of the heterodyne signal via Brownian motion, from the ratio ofintensities of light scattered at two angles in the size region wherethe ratio is an accurate indicator of size, or by other size measurementtechniques. This scattering model could then be used for computations ofparticle size in a counting process, which does not use Brownian motion.

Other methods of generating the heterodyne local oscillator are alsoclaimed in this disclosure for systems like in FIG. 19. For example asmall reflecting sphere or scattering object could be placed in theinteraction volume to scatter or reflect light into the heterodynedetectors along with the light scattered by the moving particle. Sincethis sphere or object is stationary, the optical phase differencebetween the scattered light from the moving particle and light scattered(or reflected) from the sphere or object would increase as the particlepassed through the beam, creating an oscillating beat scatter signal onthe detectors, at high frequencies. Then the local oscillator beam,which passes through lens 1906, could be eliminated.

In FIG. 19, the effective scattering angles seen by each detector candepend upon the position of the particle in the beam. The addition oflenses 2407 and 2408, as shown in FIG. 24 (which only shows thedetection portion of FIG. 19), will lower the scatter angle sensitivityto particle position. Each of these lenses place the detectors in aplane which is conjugate to the back focal plane of either lens 2403 orlens 2404. Essentially the back focal plane of lens 2403 is imaged bylens 2407 onto detectors 2413 and 2414; and the back focal plane of lens2404 is imaged by lens 2408 onto detectors 2411 and 2412. Also thedetectors could be placed in the back focal planes of lens 2407 and lens2408, where each point in the focal plane corresponds to the samescattering angle from any point in the interaction volume. Thisconfiguration nearly eliminates dependence of detector scattering angleson the position of particles in the beam. However, in many cases thisangular dependence is negligible and the additional lenses are notneeded.

By powering the source at various intensity levels, the scattered lightfrom particles which span a large range of scattering intensities can bemeasured with one analog to digital converter. Even though the dynamicrange of the scattered light may be larger than the range of the A/D,particles in different size ranges can be digitized at different sourceintensity levels. The resulting signals can be normalized to theircorresponding source intensity and then used to determine the size ofeach particle.

In FIG. 11, the 2-Dimensional detector array could also be moved fartheraway from lens 1104 to the plane which is nearly optically conjugate tothe center of the sample cell. This may provide better imagingresolution of the particles on the array.

Also it is recognized that many of the ideas in this disclosure haveapplication outside of particle counting applications. Any otherapplications for these ideas are also claimed. In particular, the ideasput forth in FIGS. 21 and 22 would also have application in ensembleparticle sizing systems.

Many drawings of optical systems in this disclosure show small sourceswith high divergence which are spatially filtered by a lens and pinholeand then collimated by a second lens. In all cases, a low divergencelaser beam could replace this collimated source, as long as the spectralproperties of the laser are appropriate for smoothing of Mie resonancesif needed.

Another issue is interferometric visibility in the heterodyne signalsdescribed before. Misalignment of beamsplitter or lenses 2405 or 2406 inFIG. 24 can lower the visibility of the heterodyne signals. Since thisloss may be different on different detectors, the ratio of two signalsmay not be preserved. However, the ratio of the visibilities for twodetectors will be the same for all particles. Therefore a correction forthe effects of low visibility, for both absolute signals and signalratios, can be determined by measuring scattered signals from one ormore nearly mono-sized particles of known size and comparing the resultswith theoretical values to determine the effective visibility for eachchannel or visibility ratio for pairs of channels. This is most easilyaccomplished by measuring larger particles with scattering signals ofvery high signal to noise and looking at the actual heterodyne signalsto determine the interferometric visibility for each detector. Thiscould be determined by blocking the local oscillator light and measuringthe scattered signal pulse with, and without, the local oscillator tocalculate the theoretical heterodyne signal from the measurement of thelocal oscillator power and the scattered pulse amplitude. Also simplycomparing the ratio of two scattering heterodyne signals to thetheoretical value for that particle size would also provide a correctionfactor for the ratio, directly.

For particles which are much smaller than the size of the laser spot,the scattered signal for particles passing through various portions ofthe laser spot will be distributed over a range of peak amplitudes. Fora group of monosized particles, the probability that a peak amplitudewill be between value S-deltaS/2 and S+deltaS/2 is Pn(S)deltaS, wherePn(S) is the probability density function for scattering amplitude inlinear S space. “deltaQ” means the difference in Q between the endpoints of the interval in Q, where Q may be S or Log(S) for example. Fora group of monosized particles of a second size (diameter D2 in FIG.25), the scattering amplitudes, S, for particles that have passedthrough the same region of laser beam, as particles of the first sizediameter D1, are changed by a multiplier R and the probability densityamplitude is changed by a multiplier of 1/R, as shown in first graph ofFIG. 25 for two particle diameters, D1 and D2 and the followingequation:

Pn(S)deltaS=Pn(RS)deltaS/R

If we switch to logarithmic space for S, we find that the probabilitydensity becomes shift invariant to a change in particle size.(Pg(Log(S)) only shifts along the Log(s) axes as R or particle sizechanges.

Using deltaS=R*deltaLog(S)

Pg(Log(S))deltaLog(S)=Pg(Log(R)+Log(S))deltaLog(S)

Where Pg(Log(S)) is the probability density function in Log(S) space.This shift invariance means that the differential count-vs.-Log(S)distribution, Cg, in logarithmic space is a convolution of theprobability function Pg shown in FIG. 25, with the number-vs.-size Ng,where all are functions of Log(S).

Cg=NgΘPg in convolution form where Pg is the response (impulse response)from a monosized particle ensemble

Cg=Ng*Pgm in matrix form, where each column in matrix Pgm is theprobability function for the size corresponding to the element of Ngwhich multiplies it. This more general equation can also be used for anycase, including when Pg is not a convolution form.

These equations can be inverted to solve for Ng, given Cg and Pg, byusing deconvolution techniques or matrix equation solutions. Pg isdetermined theoretically from the laser beam intensity profile orempirically from the Cg measured for one or more monosized particlesamples. If the shape of Pg has some sensitivity to particle size, thematrix equation is preferable.

These relationships also hold for the above functions, when they arefunctions of more than one variable. For example, consider the casewhere Cg is a function of scattering values S1 and S2 from twoscattering detectors at different scattering angles. Then Pg and Cg are2-dimensional functions because they are functions two variables ordimensions. Then Cg(Log(S1),Log(S2))deltaLog(S1)deltaLog(S2) is thenumber of events counted with log signals betweenLog(S1)−delta(Log(S1))/2 and Log(S1)+delta(Log(S1))/2, and betweenLog(S2)−delta(Log(S2))/2 and Log(S2)+delta(Log(S2))/2. ThenCg(Log(S1),Log(S2)) could be plotted as a surface on the(Log(S1),Log(S2)) plane as shown in FIG. 26. This surface is determinedfrom the event density of the “scatter plot” or “dot plot” of all of theparticles on the Log(S1),Log(S2) plane (each particle is represented byits values of Log(S1) on the X axis and Log(S2) on the Y axis on thescatter plot). So an event is the dot or point in Log(S1),Log(S2) space(or S1,S2 space) which represents a counted object. The distributionfunctions Pg and Cg are calculated from the number of events for eachsmall area in this space. The two dimensional space is divided up intosmall squares. The number of events or counts are summed inside eachsquare and the value of that sum is placed at the center of that square.These summed values then create the sampled values of Pg or Cg at thoselocations on the 2-dimensional Log(S1): Log(S2) plane. Then functions ofthese two variables can be fit (using regression analysis orinterpolation) to these sampled values to provide continuous functionsof Cg and Pg over the entire 2-dimensional surface. Each square shouldbe of sufficient size to prevent large count errors within the squaredue to Poisson statistics. Hence the sizes of the squares may vary toaccommodate the local count density in each region of the plot. Thisconcept can be extended to any number of scattering parameters anddimensions. For example, for functions of 3-dimensions, the squareswould become cubes. A group of monosized particles will theoreticallyproduce a group of points in S1,S2 space which follow the functionLog(S2)=Log(S1)+Log(R). Hence the data points will line up along a lineof slope=1 and with an offset of Log(R). R is particle size dependentover a certain size range. The distribution of points along the lengthof the line for the particle group is determined by range of S1 and S2for that group due to the intensity distribution of the source beam. Ifparticles pass through the beam at random locations, the distribution ofdata points along the line will follow the intensity distribution alongeach of the S1 and S2 axes. R, which is the ratio between S2 and S1,changes with particle size. As the particle size decreases below thewavelength of the source, R becomes a constant for all sizes, asdetermined from Rayleigh scattering theory. However, real measurementsdo not follow theory exactly due to structural imperfections in theoptical system. These imperfections will cause broadening of the line.This broadening is illustrated by an elliptical shape (however theactual shape may not be elliptical) in FIG. 26. Each ellipse representsthe approximate perimeter around a group of counted data points on theS1,S2 plane from particles all of one size. The actual shape of thisperimeter may not be an ellipse, depending upon the source ofbroadening. Notice, if the only cause of response broadening is due tothe intensity distribution of the source spot, then the ellipses in FIG.26 will collapse to line segments along the major axes of each ellipse,because both signals from each point will have nearly the same ratio forparticles of the same size. If the peak value of the scatter signal ismeasured, the ellipse perimeter will collapse to a smaller region,because the intensity variations of the source in the flow directionwill not effect the broadening of the response. The broadening will bedue to the change in peak intensity for different particle paths thoughthe beam.

A group of monosized particles will produce a differential countdistribution in S1,S2 or Log(S1),Log(S2) space. In each case, adifferential count distribution from a polysized sample will be the sumof the monosized distributions, each weighted by the percentage ofparticles of that size in the total distribution. Hence the particlenumber-vs.-size distribution can be determined by inverting this totaldifferential count distribution, as a function of S1 and S2, or Log(S1)and Log(S2), using deconvolution algorithms which may include thosealready developed for image restoration or image deblurring. Examples ofthese 2-dimensional deconvolution algorithms are Wiener filter andLucy-Richardson algorithm. In Log(S1),Log(S2) space the monosizedresponse functions will be similar in shape over a large size range,because the functions are approximately shift invariant to size over theLog(S1),Log(S2) space. In this logarithmic space, deconvolution can beused to invert the count distribution in either one or more dimensions.The signal pulse from each event may pass through an analysis or sortingas described before, to sharpen the monosized response for higher sizeresolution. These pre-processed pulses are counted vs. a parameter (S1,S2, etc) such as peak value, total area, total correlated signal, etc.,using the methods outlined previously. Each counted event is placed intothe S1,S2 or Log(S1),Log(S2) space, where S1 and S2 may be the pulsepeak value, pulse area, or any of the other size related parameterswhich can be calculated from the scattering signals. Then this space isbroken up into very small regions, and the events in each region aresummed to give sampled values of the differential count-vs.-parameterdistribution (the 2-dimensional Cg is an example of this distribution)in the 2 dimensional space. The known monosized response (in the 2dimensional space), which may be size dependent, is used to invert thisdifferential distribution to produce the particle number vs. sizedistribution. This monosized response may be calculated from scatteringtheory and the optical design parameters, or it may be measuredempirically by recording the differential event count distribution inthe space from monosized particle groups of known sizes. The knownmonosized response defines a region in the space, where scattering fromsingle particles can produce counts as shown in FIG. 27. Events whichare outside of this region, can be rejected as non-particle events (i.e.non-single particle events or noise), which may be due to multipleparticles in the interaction volume or noise. This is particularlyimportant for small sized particles with low scattering signals, wheredetection noise can cause many non-particle counted events as shown inFIG. 28. These noise events can also be included into the monosizedresponse functions. For example, when a group of monosized particles aremeasured to produce an empirical monosized response function, many noiseevents will be measured. These noise events can be included in themonosized response function so that they are removed as part of theinversion process, when that function is used as one of response set inthe inversion algorithm. The complete monosized response function setcan be generated from scattering data from only a few well chosenmonosized particle groups. The intervening response functions areinterpolated from the trend of the theoretical scattering/optical systemmodel. The empirical data from monosized samples may only be needed tolocate the theoretical model in the space. The power of this process isthat both the absolute signal data, which is needed to size particles inthe Rayleigh scattering regime, and the scattering signal ratioinformation are combined into one space, where non-particle events areeasily identified. This process can be applied to data taken in anynumber of dimensions, from one scattering angle to any number ofscattering angles. Also any dimension of this process can be representedby a scattering signal related parameter (peak, integral, etc.) orcombination of scattering signals (ratio of S2/S1, correlation betweenS2 and S1, etc.). Higher number of dimensions provides betterdiscrimination against non-particle events, but with added cost of moredetectors and computer processing time. For example, more than twodetectors could be placed behind each of slit 114 or slit 115 (aperture1 or aperture 2), in the previous figures, to provide additionaldimensions to the problem. For 3 detectors you could plot each event onthe S3/S1, S2/S1 plane. Then the effects of source spot intensityvariations would be reduced and the impulse responses (the ellipsesshown previously) would become very localized, perhaps eliminating theneed for deconvolution. All four detectors from these figures (detectors110, 111, 112, 113) could also be combined into one four dimensionalspace as described in this section or into two 2-dimensional spaces,which are first solved separately and then the results are combined intoone final size distribution by blending methods described previously.

If all of the particles in a particular sample are in a size regionwhere the signal ratio is not sensitive to particle size, such as theRayleigh size regime, the scattering model could be determinedempirically from dynamic scattering measurements. If the particle flowis stopped, the heterodyning detection system can measure the Dopplerspectral broadening due to Brownian motion (dynamic light scattering).The particle size distribution from this measurement may be useddirectly, or the optical scattering model may be determined from thedynamic scattering size distribution and the static angular scatteringto invert the absolute scattering signal amplitudes from thecount-vs.-scattering signal distribution. In this way, the low sizeresolution distribution from dynamic light scattering will providescattering model selection for the higher size resolution countingmethod. This technique can be used over the entire size range of thedynamic light scattering to select the scattering model for countingparticles inside or outside of the size range of dynamic lightscattering. The scattering model may also be determined by inverting thecount distribution in S1,S2 or Log(S1),Log(S2) space. This inversionwill create a line function in the space. The shape of this linefunction in the size transition from Rayleigh scattering (where theratio between S1 and S2 is constant) to larger particles will indicatethe scattering model and refractive index of the particles.

This multi-parameter analysis also provides for separation of mixturesof particles of different compositions such as polymer particles mixedwith metal particles or polymer particles mixed with air bubbles. Hence,the count of air bubbles could be eliminated from the countdistribution. FIG. 27 a shows the methodology. Particles of differentcomposition will have different response profiles in themulti-dimensional space. And the count events will be grouped to followdifferent profiles for each particle composition. So the data points(events) for particles of different composition will occupy differentresponse profiles as shown in FIG. 27 a. Individual particle sizedistributions and particle concentrations, for each particle type, couldbe determined from analysis of this data using the techniques describedin this disclosure, individually for each response profile. Hence, adifferent particle refractive index and optical scattering model wouldbe determined and used to calculate the size distributions for particlesin each composition group, separately. Particle counts due to airbubbles could be eliminated through this process. These techniques couldalso be extended to larger numbers of dimensions by measuring moresignals.

This process could also be used by replacing signals, in these multipleparameter plots, with ratios of signals. Any of these multiple angleconfigurations may be extended to many more angles simply by adding morescatter detectors which view the same interaction volume. For example,consider 4 such detector signals, S1, S2, S3, S4. Each of these signalscould be pulse peak, pulse area, or correlated peak, etc. The ratiosS4/S1, S3/S1, and S2/S1 are plotted in 3-dimensional space, one pointfor each particle counted. These ratios could also be S4/S2, S3/S2,S2/S1, etc. The point here is that the Mie resonances cause thescattering signals at various angles to oscillate together vs. particlesize. For any size range, there is always a region of scattering angleswhere the ratio of scatter from two different ranges of angle are nearlyindependent of Mie resonances and particle composition. The path ofthese ratios in 2-dimensional space (e.g. S3/S1,S2/S1) or 3-dimensionalspace (e.g. S4/S1,S3/S1,S2/S1), are only weakly dependent on particlecomposition. The strongest particle composition dependence is forspherical particles in the size region of the Mie resonances. Whenthousands of particles are measured, their points will follow amulti-dimensional curve or line, in this multi-dimensional space, whichindicates the sphericity or composition of the particles. Thismulti-dimensional line is formed by the highest concentration of pointsin this multidimensional space. Only points which are within a certaindistance of this line are accepted as true particles. The outliersrepresent particles which passed through the edge of the source beam orwhose signals are contaminated by noise. Also non-single particleevents, such as noise pulses or multiple particles, would also berejected because their combination of coordinates in this space wouldnot agree with the possible coordinates of a particle. The signal ratioscould also be replaced by the signal values to take advantage ofabsolute signal information, which is particularly advantageous in theRayleigh region where signal ratios are weakly dependent on particlesize, but absolute signal levels are strongly dependent on particlesize. For particles of size above the Rayleigh region, the signal ratiosmay be preferred because the spread of particle events around themulti-dimensional line is very small for signal ratios which remove thedependence upon the particle position in the beam, removing a portion ofthe monosized response broadening shown in FIGS. 27 and 28. Both of thetechniques, described here and in the description of FIGS. 27 and 28,will be needed to cover the entire size range, because the signal ratiosare not strongly size dependent in the Rayleigh region (for particlesbelow 0.1 micron in visible light). Another option would be to use amulti-dimensional space where some dimensions were signal ratios andother dimensions where absolute signals (for example see FIG. 39). Thenthe monosized response would only be strongly broadened in the absolutesignal dimensions. For small particles, the absolute signal dimensionwould be processed with deconvolution and noise event rejection as shownin FIGS. 27 and 28; and for larger particles, signal ratio dimensionswould be used to determine size with outlier rejection and minimaldeconvolution. The entire path of the line constructed by the particleevents determines the optical scattering model. This is particularlyimportant for the Rayleigh region where the particle refractive indexmust be determined to calculate the dependence of absolute scatteringamplitude on particle size. In any case, there will be a line or curve,in multi-dimensional space, which follows the path defined by thehighest concentration of counted events. This line will define theoptical scattering model and the particle shape or composition, if theuser cannot provide that information. Size accuracy may be improved byusing any apriori information about the particles to determine thescattering model from theoretical models. For example, the path of themulti-dimensional line could be calculated from scattering theory, giventhe particle refractive index and shape, but sometimes this informationis not well known. If the particle composition or shape is unknown, thenthis empirically determined line in multidimensional space is comparedto the theoretical lines for particles of various compositions andshapes. The theoretical line, which most closely matches the measuredline from the unknown particle dispersion, is assumed to represent thecomposition and shape of the unknown particles.

The accuracy of the process described above improves as more scatteringangles are measured. For example, the measured values of the scatteredlight for each of three scattering angles could be measured for eachparticle. These data points are then analyzed in a three dimensionalscatter or dot plot. A line could be generated in 3 dimensional space bydetermining the path where the maximum concentration of particles (ordots in the plot) reside. In any one axis, this line may be multi-valuedvs. particle diameter, especially in the region of Mie resonances.However, the line will not be multi-valued in 3 dimensional space. Thespread of points about this line will be determined by the intensitydistribution of the source beam in the interaction region. This group ofpoints could be deconvolved in 3 dimensional space to produce a moresharply defined set of points, with less spread from the line, providingbetter size resolution along the line. But a better solution is tomeasure 4 scattering values at 4 different scattering angles for eachparticle. And then take ratio of each of any 3 values with the fourthvalue (or any other value) to remove the effect of intensity variationfor particles which pass through different portions of the beam. Producea scatter plot of these 3 ratios in three dimensions, where each pointin 3 dimensional space is placed in Xm, Ym, and Zm values correspondingto the three ratios for each particle. Since the intensity distributionbroadening is reduced, most of the points will tightly follow a line inthree dimensional space. Outliers which are not close to the linepassing through the highest concentration of data points may beeliminated as not being real single particles. The remaining data points(Xm,Ym,Zm) are then compared to different theoretical models todetermine the composition and/or shape of the particles. The 3dimensional function which describes the theoretical scattering is Ztwhere Zt is a function of Xt and Yt

Zt=Zt(Xt,Yt)

Let (Xm,Ym,Zm) be the set of data points measured from the countedparticles. Where the values in the X,Y,Z coordinates represent theabsolute scattering signals S1, S2, S3, the logarithms of these signals,signal ratios S4/S1, S3/S1, S2/S1 (or any other combination of ratios),or any other signals or parameters mentioned in this application. Thendefine an error function Et for a certain theoretical model as:

Et(Xm,Ym)=(Yt(Xm)−Ym)̂2 for Xm in the region Xmy where Yt(Xm) issingle-valued

Et(Xm,Zm)=(Zt(Xm)−Zm)̂2 for Xm in the region Zmy where Zt(Xm) issingle-valued

Where Yt(Xm) is the theoretical value of Yt at Xm and Zt(Xm) is thetheoretical value of Zt at Xm. Then find the theoretical model whichproduces the minimum sum of Esum over all values of Xm in the data set.

Esum=SUM(Et(Xm,Ym))/Ny+SUM(Et(Xm,Zm))/Nz

Where Ny is the number of points in region Xmy and Nz is the number ofpoints in Xmz. And SUM is the sum of Et over its valid region of Xmy orZmy. Esum is calculated for various theoretical scattering models, forspherical and non-spherical particles, and the model with the lowestEsum is chosen as the model for the sample. The sum of Esum values frommultiple particle samples can also be compared for different theoreticalmodels. The model with the lowest sum of Esum values is used to analyzeall of those samples of that type. This calculation may becomputationally intensive, but it only needs to be done once for eachtype of sample. Once the optimal theoretical model is determined foreach particle sample type, the appropriate stored model can be retrievedwhenever that sample type is measured. The chosen theoretical model willprovide the particle diameter as a function of Xm, Ym, and Zm for eachdetected object.

Signal ratios show reduced sensitivity to the position of the particlein the source beam because each scattering signal is proportional to theoptical irradiance on the particle. Usually to obtain optimal signal tonoise, a laser source will be used to provide high irradiance but withlower irradiance uniformity due to the Gaussian intensity profile. Thebroadening in the monosized response, as shown in FIGS. 27 and 28 forexample, may be reduced by insuring that only particles which pass nearto the peak of the beam intensity profile are counted. Many methods havebeen described above to accomplish this selection process. Other methodscould include the use of small capillaries or sheath flow to force allof the particles to go through the center of the source beam. But thesemethods are sometimes prone to particle clogging. In sheath flow, theparticle dispersion is restricted to flow through a narrow jet, which issurrounded by a flow sheath of clean dispersant. If the particleconcentration is low, the particles in this narrow stream will passthrough the laser in single file and in locations close to the center ofthe beam. This method could be used with the ideas in this disclosure torestrict the path of the particles through the source beam and provide asingle size response with less broadening. But the wide range ofparticle sizes would require many different sized jets to handle theentire size range with the constant danger of clogging. The methodsdescribed in this disclosure can be used within a flow system of muchlarger dimensions, because the optical system only views and countsparticles within a small interaction volume of that much larger volume.Particles which pass through that volume and which are outside of thesize range for that measurement system will produce data points in themultidimensional space which are far from the multi-dimensional line ofthe optical model. They may be rejected based upon this criteria orsimply based upon the length of the scattering pulse. The smallparticles are counted and sized by the higher angle system. The largerparticles are sized by the 2-dimensional array or lower angle scatteringsystems. These independent particle size distributions are then combinedto produce one size distribution over the full size range of theinstrument.

The measurement of particle shape has become more important in manyprocesses. Usually the shape can be described by length and widthdimensions of the particle. If the length and width of each particlewere measured, a scatter plot of the counted particles may be plotted onthe length and width space to provide useful information to particlemanufacturers and users, and this type scatter plot is claimed in thisinvention. If the particles are oriented in a flow stream, the angularscattering could be measured in two nearly orthogonal scattering planes,one parallel and one perpendicular to the flow direction. Each of thesescatter detection systems would measure the corresponding dimension ofthe particle in the scattering plane for that detection system. If theflow of particle dispersion flows through a restriction, so as to createan accelerating flow field, elongated particles will orient themselvesin the flow direction. FIG. 29 shows one of these scatter detectionsystems where the scattering plane is parallel to Ys and measures theprojected particle dimension in the Ys direction, which is parallel tothe projection of the flow direction of the particles in the Ys/Xsplane. A second scattering detection system could be placed in ascattering plane which includes the Z axis and Yp as shown in FIG. 30.This detection system would measure the particle dimension in the planeperpendicular to the flow. Each particle is counted with two dimensions,one parallel to and the other perpendicular to the flow, as measuredconcurrently by these two detection systems. In some cases, theparticles cannot be oriented in the flow and they pass through the beamin random orientations. The detection configuration in FIG. 31 showsthree scattering systems. Each system is in a scattering plane which isapproximately 120 degrees from the next one. If the particle shapes areassumed to be of a certain type with two dimension parameters such as:rectangular, ellipsoid, etc., three size measurements in variousscattering planes can be used to solve for the length, width, (or majorand minor axis, etc.) and orientation of each particle. These planes canbe separated by any angles, but 120 degrees would be optimal to properlycondition the 3 simultaneous equations formed from these three sizemeasurements.

When measuring larger particles, which require smaller scatteringangles, the scatter collection lens may be centered on the Z axis, withscattering detectors in the back focal plane of the collection lens, asshown in FIG. 32. As shown before, lens 3201, pinhole 3211, and lens3202 are not needed if a spatially clean collimated beam, such as aclean laser beam, is incident on the particle dispersion in the samplecell. Lens 3203 collects scattered light from the particles and focusesit onto a group of detectors in the back focal plane. As before, thelength and width of each randomly oriented particle is determined by 3independent size measurements or, in the case where the sizemeasurements are not independent, you must solve a set of simultaneousequations as described below. If the particles are oriented in the flow,only the Ys direction (parallel to the flow) and a set of detectors inthe direction perpendicular to Ys are needed. As before, these twodirections can be at any angle, but parallel and perpendicular to theflow are optimal. In the random orientation case, each measurement ismade by a separate arm of the detector set in the three directions Ys,Y1, and Y2. These directions can be separated by any angles, but 120degrees (see FIG. 33) would be optimal to properly condition the 3simultaneous equations formed from these three size measurements. Thescatter detector signals in each direction (or scattering plane) arecombined by ratio of signals or other algorithms to determine theeffective size in that direction. Then three simultaneous equations areformed from these size measurements to solve for the width, length, andorientation of each particle. FIG. 34 shows how this detectorconfiguration is used in the system from FIG. 11. And as indicatedabove, the scatter in various scattering angular ranges can be measuredeach scattering plane by a separate optical system, as shown in FIG. 29for example, in each scattering plane. The scattering plane is the planewhich includes the center axis of the source beam and the center axes ofthe scattered light beams which are captured by the detectors.

The accuracy of the methods outlined above is improved by solvinganother type of problem. The sizes calculated from angular scatteringdata in each of two or more directions are not usually independent. Inorder to accurately determine the shape parameters of a particle, thesimultaneous equations must be formed in all of the scattering signals.The form of the equations is shown below:

Si=Fi(W,L,O)

Where Si is the scattering signal from the ith detector. In the case ofthree directions (or scattering planes) and three detectors perdirection, we have 9 total detectors and i=1, 2, . . . 9)

W is the “width” parameter and L is the “length” parameter of theparticle. In the case of a rectangular shape model, W is width and L islength. In the case of an ellipsoidal model, W is the minor axis and Lis the major axis, etc. O is the orientation of the particle which couldbe the angle of the particle's major axis relative to Ys, for example.The functions Fi are calculated from non-spherical scattering algorithmsand the form of Fi changes for different particle shapes (rectangles,ellipsoids, etc.). These equations, Si=Fi, form a set of simultaneousequations which are solved for W, L and O for each particle. If the Fifunctions do not have a closed form, iterative methods may be employedwhere the Jacobian or Hessian are determined by numerical, rather thansymbolic, derivatives. Also the closed form functions for Fi could beprovided by fitting functions to Fi(W,L,O) calculated from thenon-spherical scattering algorithms.

If we had two detection angles per each of three scattering planes, wewould have 6 equations with 3 unknowns. With three detectors perscattering plane the size range may be extended and we will have 9equations with 3 unknowns. For particles with more complicated shapes,such as polygonal, more scattering planes may be required to determinethe particle shape parameters. In any case, a shape model is assumed forthe particles and the set of equations Si=Fi are created for that modelwhere Fi is a function of the unknown size parameters and Si is thescattered signal on detector i. This method can be applied to any of theshape measuring configurations shown before. This technique can also beapplied to ensemble size measuring systems when the particles all havethe same orientation as in accelerating flow. This invention claimsscattering measurements from any number of angular ranges, in any numberof scattering planes.

Low scattering signals from small particles may be difficult to detect.FIG. 35 shows another variation where the source beam is passed througha patterned target which is conjugate to the interaction volume. Theimage of the target occurs in the interaction volume which is defined byaperture 3501 or aperture 3502. This target could consist of asinusoidal transmission pattern or a Barker code pattern. As theparticles pass through the image of this pattern, the scattered light ismodulated by the modulated source intensity distribution in theinteraction volume and so the scattered signal-vs.-time distribution isequivalent to the spatial intensity distribution. For a sinusoidalpattern, a phase sensitive detector with zero degree and quadratureoutputs could be used to detect the sinusoidal signal of arbitraryphase. For a given particle velocity, the scattered signal could befiltered by a bandpass filter which is centered on the frequency equalto the particle velocity divided by the spatial wavelength of thesinusoidal intensity distribution in the interaction volume. The phasesensitive detector reference signal would also match this frequency.Better signal to noise may be achieved with other types of patterns. ABarker code target pattern will produce a single peak with very smallside lobes when the scattering signal is correlated with a matchingBarker code signal using a SAW or CCD correlator. When two scatteringsignals are multiplied and integrated, the zero delay (tau) value of thecorrelation function is obtained. This value will have the lowestfluctuation when the two signals have strong correlation as when bothsignals are from the same particle, instead of uncorrelated noise. Theintegrated product of the two signals will show less noise than theseparated integrated signals. So the product of signals from twodifferent angular ranges or the integral of this product over theparticle pulse period will provide a signal parameter which is lesssensitive to noise and which can be substituted for Si in any of theanalyses described above. FIG. 35 also illustrates an additionalscattering detector on aperture 3502 for detection of three scatteringangles. This can also be extended to a larger number of detectors.

As shown before, ratios of scattering signals can be analyzed as amulti-dimensional function. Another method is to look at the individualsignal ratios vs. particle diameter as shown in FIG. 36 for the case ofthree signal ratios. Any real particle event should produce a point oneach curve which align vertically at the same diameter. Each curveindicates the particle size, but the most accurate size is determinedfrom the curve where its point is in a region of high slope andmonotonicity. For any particle, the 3 measured ratios would determinethe approximate particle size region and allow selection of the oneratio which is in the region of highest slope vs. particle size and isalso not in a multi-valued region (caused by Mie resonances). Thisselected ratio would then be used to determine the precise particle sizefor that particle.

The ratio of scattering signals from different scattering angles reducesthe dependence of the particle size determination on the particle paththrough the light beam. Particles with signals below some threshold areeliminated from the count to prevent counting objects with low signal tonoise. The accuracy of counts in each size bin will depend upon howuniform this elimination criteria is over the entire size range. Manymethods have been described in this application for reducing thisproblem. These methods are improved by having a source beam with a “flattop” intensity distribution and very sharply defined edges. This flattop intensity distribution can be provided by placing an aperture in anoptical plane which is conjugate to the interaction volume or by usingdiffractive optic or absorption mask beam shapers. Another techniquewhich will accurately define an interaction volume is shown in FIG. 37.No selection criteria is required for the direction which is parallel tothe particle flow direction, because in this direction each particlepasses through a similar intensity distribution and digitized signalvalues may be analyzed to find maximum or the integral for each particlesignal. The primary criteria for eliminating particles from the count isbased upon the position of the particle along the axis which isperpendicular to particle flow direction. The position of the particlealong the direction perpendicular to the particle flow and thescattering plane (y direction) can be determined by using a 3 elementdetector which is in an optical plane which is conjugate to theinteraction volume as shown in FIG. 37. This figure shows the positionand orientation of the 3 element detector in the optical system and anenlarged view of the detector elements showing the path of variousparticles passing through the interaction volume as seen by the detectorelements. The beamsplitter, following lens 3703, splits off somescattered light to the 3 element detector. By measuring the signal ratiobetween elements 1 and 2 and the ratio between elements 3 and 2, the yposition of the each particle is determined and only particles within acertain y distance from the center of the light beam are accepted. Ifboth ratios are equal, the particle is in the center of the 3 detectorarray. If one ratio is higher than the other, the particle is shiftedcloser to element whose signal is in the numerator of that higher ratio.This signal ratio criteria is extremely accurate and uniform among allparticle sizes so that proper mass balance is maintained over the entiresize range. The ratio is also insensitive to how well the particle isoptically resolved because the fraction the particle image on each thetwo detectors spanning the image is not strongly dependent on the sizeor sharpness of the image, but is strongly dependent on the y positionof the particle. FIG. 37 shows the 3 element detector in a heterodynearrangement, with a portion of the source light being mixed with thescattered light. However, this idea is also applicable to non-heterodyneconfigurations by just removing the beamsplitter between lens 3701 andlens 3702. And this method can also be applied to any other scatterdetection system in this application by placing this three elementdetector in an image plane of the particles, through a beamsplitter. Theorientation of the 3 element array relative to particle motion is shownin FIG. 37.

Many figures (FIG. 19 for example) show the heterodyne system with anegative and positive lens pair (lenses 1905 and 1906) which provide alocal oscillator beam which matches the wavefront of scattered lightfrom the particles. FIG. 38 shows an alternative design where all beamsare nearly collimated in the regions of the beamsplitters. Thisconfiguration may be easier to align and focus. Lens 3801 collimates thesource light which is sampled by beamsplitter 3821 and directed tobeamsplitter 3822 by the mirror. Lens 3803 collimates the lightscattered by the particle and this light is combined with the sourcelight by beamsplitter 3822 and focused through aperture 3832 by lens3807. As before, aperture 3832 is conjugate to the particle interactionvolume and defines the interaction volume, in the sample cell, which isviewed by the detectors 3813, 3814 and 3815. Usually, the focal lengthof lens 3802 is long to provide a source beam of low divergence and thefocal length of lens 3803 is short to span a large range of scatteringangles. If the light source is a laser diode, without anamorphic optics,the major axis of the intensity distribution ellipse at the interactionvolume should be in the plane of the particle flow and scattering planeto provide a long train of heterodyne oscillations for signal detectionand to provide the lowest beam divergence in the scattering plane. Acircular source beam may require anamorphic optics to create anelliptical beam in the interaction volume to provide the advantagesmentioned above. However, the advantages of the ideas described in thisdisclosure can be applied to a source beam with any intensitydistribution.

The matching of light wavefronts between the source beam and scatteredlight at the heterodyne detectors is important to maintain optimuminterferometric visibility and maximum modulation of the heterodynesignal on each detector. Since perfect wavefront matching is notachievable, the interferometric visibility must be determined for eachdetector to correct the signals for deviation from theoreticalheterodyne modulation amplitude. The visibility is determined bymeasuring particles of known size and comparing the heterodyne signalsto the signals expected from theory. To first order, the interferometricvisibility should be independent of particle size for particles muchsmaller than the source beam in the interaction volume. The visibilitycould be measured for particles of various sizes to measure any secondorder effects which would create visibility dependence on particle size.If only signal ratios are used for determining size determination, onlythe ratios of interferometric visibility need to be calibrated bymeasuring scattering from particles of known size.

The number of cycles in the heterodyne modulated pulse is determined bythe length of the trajectory of the particle through the source beam.The frequency of the heterodyne modulation is determined by the velocityof the particle through the beam. In general the power spectrum of thesignal will consist of the spectrum of the pulse (which may be 10 KHzwide) centered on the heterodyne frequency (which may be 1 MHz). Both ofthese frequencies are proportional to the particle velocity. Actuallythe best frequency region for the signal will be determined by the powerspectral density of the detector system noise and/or the gain-bandwidthproduct of the detector electronics. For this reason, in some cases theparticle flow velocity should be lowered to shift the signal spectrum tolower frequencies. The particle concentration is then adjusted tominimize the time required to count a sufficient number of particles toreduce Poisson statistic errors. This is easily accomplished for smallparticles which usually have higher count per unit volume and requirelower noise to maintain high signal to noise.

In cases where optical heterodyne detection is not used, the signal tonoise may be improved by phase sensitive detection of the scatteredlight. Modulation of the optical source may provide for phase sensitivedetection of the scattering signal. The source is modulated at afrequency which is much larger than the bandwidth of the signal. Forexample, consider a source modulated at 1 megahertz with a scatteringpulse length of 0.1 millisecond. Then the Fourier spectrum of scatteredsignal pulse would cover a region of approximately 10 KHz width centeredat 1 megahertz. If this signal is multiplied by the source drive signalat 1 megahertz, the product of these two signals will contain a highfrequency component at approximately 2 megahertz and a differencefrequency component which spans 0 to approximately 10 KHz. In order toeliminate the most noise but preserve the signal, this product signalcould be filtered to transmit only the frequencies contained in thescattering pulse, without modulation (perhaps between 5000 and 15000Hz). This filtered signal product will have higher signal to noise thanthe raw signal of scattered pulses. This signal product can be providedby an analog multiplier or by digital multiplication after both of thesesignals (the scattering signal and the source drive signal) aredigitized. This product is more easily realized with a photon multipliertube (PMT) whose gain can be modulated by modulating the anode voltageof the PMT. Since the PMT gain is a nonlinear function of the anodevoltage, an arbitrary function generator may be used to create PMT gainmodulation which follows the modulation of the source. The voltageamplitude will be a nonlinear function of the source modulationamplitude, such that the gain modulation amplitude is a linear functionof the source modulation amplitude. An arbitrary function generator cangenerate such a nonlinear modulation which is phase locked to the sourcemodulator.

As described at the beginning of this disclosure, multiple sized beamscan also be used to control the effects of seeing more than one particlein the viewing volume at one time. The key is to choose the properscattering configuration to provide a very strong decrease of scatteringsignal with decreasing particle size. Then the scattering signals fromsmaller particles do not affect the pulses from larger ones, because thesmaller particle signals are much smaller than those from the largerparticles. For example, by measuring scattered light at very smallscattering angles, the scattered light will drop off as the fourth powerof the diameter in the Fraunhofer regime and as the sixth power ofdiameter in the Rayleigh regime. In addition, for typically uniformparticle volume vs. size distributions, there are many more smallerparticles than larger ones. The Poisson statistics of the countingprocess will reduce the signal fluctuations for the smaller particlesbecause individual particles pulses will overlap each other producing auniform baseline for the larger particles which pass through asindividual pulses. This baseline can be subtracted from the largerparticle pulse signals to produce accurate large particle pulses. Thismethod can be used in many of the systems in this application, where alarge increase in scatter signal level occurs between large and smallparticles. One example of this method is shown by the opticalconfiguration in FIG. 41.

FIG. 41 shows an optical system where the light source is spatiallyfiltered by lens 4101 and pinhole 4111. Lens 4102 collimates andprojects the source beam through the particle sample and an aperturemask, which is imaged onto the detector array by lens 4103. Lens 4102could also focus the beam into the sample cell to increase lightintensity. An annular spatial mask is placed in the back focal plane oflens 4103 to only pass scattered light over a certain range of scatterangle as defined by the inner and outer radii of the annular filter,which is similar to mask 1250 shown in FIG. 12. The very low anglescattering and incident beam are blocked by central stop of the annularaperture in the back focal plane of lens 4103. Hence the detector array1 sees an image of mask apertures and each detector element measures thescattered light only from particles in it's corresponding mask apertureover the angular range defined by the aperture (or spatial mask) in theback focal plane of lens 4103. Each detector element is equal to orslightly larger than the image of the corresponding mask aperture at thedetector plane, but each detector only sees the light from only it'scorresponding mask aperture. This configuration creates multipleinteraction volumes of differing sizes in a single source beam. Thesmaller sized apertures will count smaller particles with lowcoincidence rates and the larger sized apertures count larger particleswhose signals are much larger than the signals from smaller particleswhich are in that larger interaction volume at the same time. FIG. 41shows 3 apertures (A, B, and C), but many more apertures andcorresponding detector elements could be added. A beam splitter splitsoff a portion of the light to a second annular filter (in the back focalplane of lens 4103) and detector array 2. The angular ranges of the twoannular filters are chosen to produce scattered values which arecombined by an algorithm which determines the size of each particle. Onesuch algorithm would be a simple ratio of the corresponding pulses fromboth arrays. And if the total scattered light is sensitive to particlecomposition, then the ratio of the two scattering signals can be used todetermine the particle size more accurately. As with all other systemsdescribed in this disclosure, these ideas can be extended to more thantwo detector arrays or more than two scattering angles, simply by addingmore annular spatial masks and detectors by using beamsplitters. And thesignals can be processed and analyzed, using the methods describedpreviously.

This configuration allows each detector element to see scatter from onlya certain aperture in the mask and over a certain scattering angle rangedetermined by it's spatial mask. If the spatial mask defines a range oflow scattering angles, the total scatter for the detectors viewingthrough that spatial mask will show a strong decrease with decreasingparticle size. The signal will decrease at least at a rate of the fourthpower of the particle diameter or up to greater than the sixth power ofthe diameter. Assuming the weakest case of fourth power, we can obtain adrop by a factor of 16 in signal for a factor of 2 change in diameter.This means that you need to control the particle concentration such thatno multiple particles are measured for the smallest particle sizemeasured in each aperture. The largest particle size which hassignificant probability of multiple particles in the aperture at onetime should produce scattering signals which are small compared to thescattering from lower size measurement limit set for that aperture.However, this particle concentration constraint is relaxed if multiplepulses are separated by deconvolution within a signal segment, as shownin FIGS. 71, 72 and 73.

One annular filter aperture could also be replaced by a pinhole, whichonly passes the light from the source (the dashed line rays). Then thesignals on each detector element would decrease as a particle passesthrough it's corresponding aperture at the sample cell. This signal droppulse amplitude would directly indicate the particle size, or it couldbe used in conjunction with the other annular signals. No limits on thenumber of apertures in the sample cell mask or of annularfilter/detector sets are assumed. More annular filter/detector sets canbe added by using more beamsplitters. Also lens 4102 could focus thesource beam into the sample cell to increase intensity and scatteringsignals. Then the annular apertures must be designed to only pass lightoutside of the divergence angle of the source beam to prevent largesource background on the detectors.

FIG. 42 shows another configuration for determining particle size andshape. The light source light is focused through pinhole 4211 by lens4201 and then focused into the sample cell by lens 4202. The beamdivergence and spot size in the sample cell are determined by the rangeof scattering angles to be measured and the size range of the particles.Essentially the spot size increases and the divergence decreases forlarger particles. The scattered light is collected by lens 4203, whichfocuses it onto many multi-element detector assemblies, which are in theback focal plane of lens 4203. Each multi-element detector has multipledetector elements which measure a certain range of scattering anglesalong various scattering planes. FIG. 42 shows an example with threescattering planes separated by approximately 120 degrees betweenadjacent planes. However, any number of scattering planes with anyangular separation is claimed in this application. Each multi-elementdetector contains a central region which either captures or passes thesource light so that it does not contaminate the measurement of thescattered light. The beam divergence will determine the size of thesource light capture region on the multi-element detectors.

Each detector element has a shape which determines how much of thescattered light at each scattering angle is collected by the detectorelement. For example detector 4221 has wedge shaped detectors whichweights scattering angles progressively. Detector 4222 has a higherorder weighting, the larger scattering angles are gradually weightedmore in the total signal for each detector element. These detectorelement shapes can take on many forms: rectangular, wedged, and higherorder. Any shape will work as long as the progression of collectionwidth of the detector is different between the two multi-elementassemblies so that when the particle pulse signals from thecorresponding detector elements of the two multi-element detectors areratioed, you obtain a ratio which is particle size dependent. Theprogression of the weighting function can also be defined by placing avariable absorbing or variable reflecting plate, over each detectorelement, which varies absorption vs. radius r from the center of thedetector assembly. This absorption plate can provide a weighting similarto that obtained by varying the width of the detector element vs. r. Andsince these size measurements are made in different scattering planes,multiple dimensions of each particle are determined separately. Ingeneral each detector element produces a signal Sab, where “a” is themulti-element detector assembly number and “b” is the element numberwithin that assembly. Then we can define Sab as:

Sab=∫wa(r)f(r,d)∂r

for the bth element in the ath assembly

Here d is the dimension of the particle in the direction of thecorresponding scattering plane. The scattered intensity at radius r fromthe center of the detector assembly (corresponding to zero scatteringangle) for dimension of d is f(r,d). And wa(r) is the angular width (orweighting function) of the detector element at radius r in assembly “a”,in other words the angle which would be subtended by rotating the rvector from one side of the element to the other side at radius r. Forthe simple 3 element assemblies shown in FIG. 42, we obtain 6 measuredvalues:

S11, S12, S13 for assembly 1S21, S22, S23 for assembly 2

The signal on each detector element will consist of pulses as eachparticle passes through the beam. The Sab values above can be the peakvalue of the pulse or the integral of the pulse or other signal valuesmentioned in this disclosure. For example, one possible case would be:

Angular width for assembly 1 w1(r)=Ar

Angular width for assembly 1 w2(r)=Br*r

For this case S11/S21, S12/S22, and S13/S23 are almost linear functionsof the particle dimension in the direction of the correspondingscattering plane. These ratio values can also be analyzed using methodsshown in FIGS. 26 through 28. These 3 dimensions can also be determinedfrom an algorithm which uses all 6 S values by solving simultaneousequations which include the interdependencies of these values on eachother, as described previously. In any event, the actual dimensions ofthe particle can be determined by assumption of a certain particle formsuch as rectangular, ellipsoidal, hexagonal, etc. More detector elementsin each assembly will produce more accurate dimensions for randomlyoriented particles. The true power of this technique is that the shapeof each particle can be determined over a large size range by measuringonly a few signals. Each element of each detector assembly could bebroken up into sub-segments along the “r” direction to provide bettersize information by measuring the angular scattering distribution ineach of the scattering planes. However, this may reduce the particlecount rate because more digitizations and data analysis may be requiredper particle.

These S values can also be analyzed using methods shown in FIGS. 26through 28, by creating two dimensional plots of absolute measurementsof S1* vs. S2*(S11 vs. S21, S12 vs. S22, and S13 vs. S23). Also avirtual 6 dimensional plot of all 6 values can be created (but notplotted). Then the same methods can be used to eliminate particles whichdo not meet criteria for having passed through the central portion ofthe beam or which are caused by noise pulses (where the absolute Svalues are not consistent with the size determined from the S ratios)

The actual particle size system may consist of systems, each which issimilar to the one shown in FIG. 42. Each system would have a differentsource beam divergence and spot size in the sample cell to accommodatedifferent size ranges. The count distributions from the systems are thenconcatenated (or blended as shown previously) into one totaldistribution over the entire size range of the product. For example, forrectangular or ellipsoidal particles, the width and length dimensions ofeach particle could be plotted on a “scatter” plot to display theinformation in a useful format.

For smaller particles, the source beam will be more focused (higherdivergence and smaller spot size in the sample cell region) into thesample cell. This will help to define a smaller interaction volume, withhigher intensity, for the smaller particles which usually have highernumber concentration than the larger particles.

FIG. 43 shows another version of this concept where the interactionvolume for particle scattering is controlled by appropriately positionedapertures and by correlation measurements between signals from differentscattering angles. The system is similar to that shown in FIG. 42. Butin this case additional apertures and lenses are added in the detectionsystem. Aperture 4321 and aperture 4322 are placed in optical planeswhich are conjugate to the source focused spot in the sample cell. Theseapertures are sized and oriented to only allow the image of the focusedspot to pass on to the multi-element detector. The source beam inaperture 4320 may have significant intensity variation so as to producea large variation in scatter signals when particles pass throughdifferent portions of the source spot in the sample cell. In this case,the size of apertures 4321 and 4322 may be reduced such that theirimages, at the sample cell, only pass the uniform portion of the sourcebeam intensity profile in the sample cell. These apertures and lens 4303limit the volume, in the sample cell, from which scattered light can bedetected by the multi-element detectors. Lenses 4304 and 4305 image theback focal plane of lens 4303 on to the multi-element detector so thatthe detector sees the angular scattering distribution from theparticles. The multi-element detectors 4311 and 4312 can also measurescattered light in the back focal plane of lens 4304 and lens 4305,respectively. The multi-element detectors 4311 and 4312 can also measurescattered light directly from apertures 4321 and 4322, without lenses4304 and 4305, respectively. Detector 4330 collects all of the lightthat is scattered in a range of scattering angles which are defined bythe annular aperture 4340 (similar to the aperture shown in FIG. 12).This detector provides a equivalent diameter based on equivalentspherical particle crossectional area, without shape dependence. In somecases the size as determined by the total scatter thorough aperture 4340will be more accurate than the particle dimensions from themulti-element detectors. For example, detector 4330 could be used todetermine the particle area and the multi-element detectors coulddetermine the aspect ratio of the particle using the ratio of thedetermined dimensions. Using the area and the aspect ratio, the actualdimensions could be determined. This may be more accurate than simplydetermining the dimensions separately using the multi-element detectorsfor particles whose major or minor axis may not line up with ascattering plane and which require the solution of simultaneousequations to determine the particle shape.

Another feature of this design is the ability to use correlation orpulse alignment to determine which particle pulses are accuratelymeasured and which pulses may be vignetted in the optical system. FIG.45 shows a crossection of the source beam focus in the sample cell. Theoutline of the beam is shown as beam edges and the outline of theoptical limits for scattered rays is shown as optical limit. Theseoptical limits are defined by the angular size of the detector elementsand the size of aperture 4321 or aperture 4322. Two extreme scatteredrays are drawn in dashed lines for scattered light at a particularscattering angle. The intersection (crosshatched area) of volume betweenthose scattered rays and the source beam is the interaction volume inwhich a detector can detect scattered light at that scattering angle.For example, consider the highest angle detector elements, 4401C and4404C (see FIG. 44) which are both in a scattering plane which isparallel to flow direction of the particles. The top portion of FIG. 45shows the interaction volume for detector element 4401C. The bottomportion of FIG. 45 shows an approximation to the interaction volumes foreach of the detector elements 4401C and 4404C. Notice that as particle Apasses through these interaction volumes, both scattering signals from4401C and 4404C will be highly correlated, they will rise and falltogether with a large amount of overlap in time. However, particle B,which is farther from best focus, will show very poor correlationbetween these two detectors. In fact the pulses will be completelyseparated in time. This pulse separation between 4401C and 4404C can beused to determine where the particle has passed through the interactionvolume; and particles that are too far from best focus can be eliminatedfrom the particle count. This correlation or pulse separation can bemeasured between any two detector elements, within a group (i.e. 4401Aand 4401C) or between groups (i.e. 4401C and 4404C). Typically thescattering plane for detector groups 1 and 4 would be parallel to theparticle flow to obtain maximum delay. The correlation or pulseseparation can be determined from the digitized signals usingalgorithms. However, this may require very high speed analog to digitalconverters and enormous computational load to obtain a high particlecount and size accuracy. Another solution is to use analog electronicsto measure the correlation or the pulse separation as shown in FIG. 46,where the P boxes are processing electronics which measure the pulsepeak (peak detector) or pulse integral. The X box is an analogmultiplier. And S1A, S1B, and S1C are the analog signals from detectorelements 4401A, 4401B, and 4401C, respectively. The following equationswill provide an estimate to the correlation between the pulses:

R12=P12/(P1*P2)

R13=P13/(P1*P3)

When R12 or R13 are small, the pulses have poor correlation and theyshould be eliminated from the count.

The delay between any two pulses from separate detector elements canalso be used to select valid pulses for counting. As the particle passesthrough the beam farther from best focus of the source beam, the delaybetween the pulses will increase. Some threshold can be defined for thedelay. All pulse pairs with delays greater than the threshold are notincluded in the count. One example is shown in FIG. 47, where the delaybetween pulses from detector elements 4401C and 4404C (see FIG. 44) ismeasured to reject particles which pass through the beam too far fromthe source beam best focus. This delay can be measured by starting aclock when the first pulse (detector 4401C) rises above threshold andstopping the clock when the second pulse (detector 4404C) rises abovethreshold, assuming that detector 4401C sees the particle first. Thedelay could also be determined from the digitized profiles of these twosignals. These methods can also be used in other systems in thisapplication such as the system showed in FIG. 78, using the detectoroptics in FIGS. 84 and 85. The same analysis will provide particlerejection criteria using detectors in the scattering plane which isparallel to the flow, such as the corresponding positive and negativescattering angle elements of scattering plane 8405 in FIG. 84.

Another criteria for pulse rejection is pulse width. As shown in FIG.45, particle B will produce a shorter pulse than particle A, because thedetector element will only see scattered light from the particle whileit is in the interaction volume (the crosshatched area) for thatparticular detector element. The pulses could be digitized and the pulsewidth would then be computed as the width at some percentage of thepulse peak height to avoid errors caused by measuring pulses ofdifferent heights. As the particle passage moves away from best sourcefocus, the pulse width will at first increase and then start to decrease(with significant change in pulse shape) as the particle passes throughthe region of smaller interaction volume. Pulses, with pulse width orpulse shape (pulse symmetry or skewness) outside of an acceptable range,will be eliminated from the particle count. Any of these techniquesdiscussed above can be implemented using digitization of the detectorelement signals and computation of parameters of interest from thatdigitized data or using analog modules which directly produce theparameter of interest (pulse delay, pulse width, pulse shape,correlation, etc.). While the analog modules may have poorer accuracy,they can be much faster than digitization and computation, allowing alarger particle count and better count accuracy.

The pulse rejection criteria described above is used to reduce thenumber of coincidence counts by using apertures to limit the volumewhich is seen by the detectors. The interaction volume can also belimited by providing a short path where the particles have access to thebeam as shown in FIG. 48. Two transparent cones are bonded to the innerwalls of the sample cell windows using index matching adhesive. The tipsof each cone is cut off and polished to either a flat or a concaveoptical surface. The optical windows and transparent cones could also bereplaced with solid cell walls with holes which are aligned to hollowtruncated cones with optical windows on the truncated tip of each cone.In this way the light travels through air or glass, except for a thinlayer of particle dispersion between the two windowed cone tips. The gapbetween the cone tip surfaces provides the only volume where the flowingparticles can pass through the source beam and scatter light to thedetectors. A dispersion with a large range of particle sizes will notclog this gap because the larger particles will flow around the gap andthe particle concentration is very low. The cone tip surfaces can betilted slightly so that the spacing between them is smaller on the sidewhere the particles enter the gap and larger where they leave the gap.In this way, particles larger than the minimum width of gap, but smallerthan the maximum gap width, are prevented from jamming inside the gap.This concept is also shown in FIG. 104 with concave surfaces to reducereflections.

The beam focus may shift with different dispersant refractive indicesdue to refraction at the flat surface on the end of each cone. Thisshift in focus and angular refraction of scattered light at a surfacecan be corrected for in software by calculating the actual refractedrays which intercept the ends of each detector element to define thescattering angular range of that element for the particular dispersantrefractive index in use. This correction is not needed for concavesurfaces, on each cone tip, whose centers of curvature are coincidentwith the best focal plane of the source between the two tips. Then allof the beam rays and scattered rays pass through the concave surfacenearly normal to the surface with very little refraction and lowsensitivity to dispersant refractive index.

Another problem that can be solved by particle counting is the problemof background drift in ensemble scattering systems which measure largeparticles at low scattering angles. An ensemble scattering systemmeasures the angular distribution of scattered light from a group ofparticles instead of a single particle at one time. This angularscattering distribution is inverted by an algorithm to produce theparticle size distribution. The optical system measures scattered lightin certain angular ranges which are defined by a set of detectorelements in the back focal plane of lens 5303 in FIG. 53. Each detectorelement is usually connected to it's own separate electronic integrator,which is connected to a multiplexing circuit which sequentially sampleseach of the integrators which may integrate while many particles passthrough the beam (see a portion of FIG. 54). So particle pulses cannotbe measured in the ensemble system.

The detector elements which measure the low angle scatter usually see avery large scattering background when particles are not in the samplecell. This background is due to debris on optical surfaces or poor laserbeam quality. Mechanical drift of the optics can cause this backgroundlight to vary with time. Usually the detector array is scanned with onlyclean dispersant in the sample cell to produce background scattersignals which are then subtracted from the scatter signals from theactual particle dispersion. So first the detector integrators arescanned without any particles in the sample cell and then particles areadded to the dispersion and the detector integrators are scanned asecond time. The background scan data is subtracted from this secondscan for each detector element in the array. However, if the backgrounddrifts between the two scans, a true particle scattering distributionwill not be produced by the difference between these two scans. A thirdscan could be made after the second scan to use for interpolation of thebackground during the second scan, but this would require the samplecell to be flushed out with clean dispersant after the particles arepresent.

A much better solution, shown in FIG. 54, is to connect each of thedetector elements, for the lowest angles of scatter, to individualanalog to digital converters or peak detectors as shown before in thisdisclosure. Then these signals could be analyzed by many of the countingmethods which are described in this disclosure. This would essentiallyproduce an ensemble/counting hybrid instrument which would producecounting distributions for the large particles at low scattering anglesand deconvolved particle size distributions from the long timeintegrated detector elements, in ensemble mode, at higher scatteringangles for the smaller particles. These distributions can be convertedto a common format (such as particle volume vs. size or particle countvs. size) and combined into one distribution. The advantage is that thefrequency range for the particle pulses is so much higher than thefrequencies of the background drift. And so these pulses can be measuredaccurately by subtracting the slowly varying local signal baseline oneither side of each pulse. At very low scattering angles, the scatteringsignal drops off by at least the fourth power of particle diameter.Therefore larger single particle pulses will clearly stand out above thebackground due to lower overlapping signal pulses from many smallerparticles which may be in the beam at any instant of time. Also thenumber concentration of larger particle will be low and provide for truesingle particle counting.

As mentioned before in this disclosure, the particle shape can bedetermined by measuring the angular distribution of scattered light inmultiple scattering planes, including any number of scattering planes.The particle shape and size is more accurately determined by measuringthe angular scattering distribution in a large number of scatteringplanes, requiring many detector elements in the arrays shown in FIGS. 33and 44. As the number of detector elements becomes large, the use ofless expensive 2-dimensional detector arrays (with rows and columns ofdetectors on a rectangular grid), such as CCD arrays, becomes moreattractive to take advantage of the economies of scale for production ofcommercial CCD cameras. The 2-dimensional scattering distribution can beconverted to optical flux distributions along each of many scatteringplanes, to use the analysis described for detectors as shown in FIG. 84.Also the flux distribution as a function of x and y coordinates on thearray can be analyzed to determine the particle size and shape. However,the use of these 2-dimensional detector arrays presents some problems,which are not associated with custom detector arrays with optimallydesigned elements as shown previously. These arrays usually have poordynamic range, poor sensitivity, poor A/D resolution, slow digitizationrates, and high levels of crosstalk between pixels (blooming forexample). Methods for mitigation of these problems are described below.

The detector array could be scanned at a frame rate, where during theperiod between successive frame downloads (and digitizations) each pixelwill integrate the scattered light flux on its surface during an entirepassage of only one particle through the source beam. Each pixel currentis electronically integrated for a certain period and then itsaccumulated charge is digitized and stored; and then this cycle isrepeated many times. During each integration period the pixel detectorcurrent from scattered light from any particle, which passes through thebeam, will be integrated during the particle's total passage through thelight source beam. Therefore the angular scattering distribution forthat particle will be recorded over a large number of scattering planesby all of the detector elements in the array. This 2-dimensionalscattering distribution could be analyzed as described previously, usinga large number of simultaneous equations and more shape parameters, byassuming a certain model for the particle shape (ellipsoidal,rectangular, hexagonal, etc.). As shown before, the particle shape andrandom orientation can be determined from these equations. Also,conventional image processing algorithms for shape and orientation canbe used on the digitized scattering pattern to find the orientation(major and minor axes, etc.) and dimensions of the scatter pattern. Theparticle size and shape can be determined from these dimensions. Alsothe particle size and shape can be determined from the inverse2-dimensional Fourier transform of the scattering distribution forparticles in the Fraunhofer size range, but with a large computationtime for each particle. The inverse Fourier transform of the2-dimensional scattering distribution, which is measured by the 2dimensional detector array, will produce an image, of the particle, fromwhich various dimensions can be determined directly, using availableimage processing algorithms.

For example, consider an absorbing rectangular particle of width andlength dimensions A and B, with both dimensions in the Fraunhofer sizerange and minor and major axes along the X and Y directions. If theparticle is not absorbing or is outside of the size range for theFraunhofer approximation, then the theoretical 2-dimensional scatteredintensity distribution is calculated using known methods, such asT-matrix and Discrete Dipole Approximation, (see “Light Scattering byNonspherical Particles”, M. Mishchenko, et al.). In the Fraunhoferapproximation, the irradiance in the scattering pattern on the2-dimensional detector array will be given by:

I(a,b)=Io*(SIN C(πa)*SIN C(πb))̂2

Where SIN C(x)=SIN(x)/x

is the irradiance in the forward direction at zero scattering anglerelative to the incident light beam direction

a=A*sin(anga)/w1

b=B*sin(angb)/w1

where:w1=wavelength of the optical sourceanga=the scattering angle relative to the incident source beam directionin the scattering plane parallel to the A dimension of the particleangb=the scattering angle relative to the incident source beam directionin the scattering plane parallel to the B dimension of the particle

The corresponding x and y coordinates on the 2 dimensional detectorarray will be:

x=F*tan(anga) and y=F*tan(angb)

The scattering pattern crossections in the major and minor axes consistof two SIN C functions with first zeros located at:

xo=F*tan(arcsin(w1/A))

yo=F*tan(arcsin(w1/B))

where F is the focal length of the lens 3203 in FIG. 32 or F=M*F3 inFIG. 49 where F3 is the focal length of lens 4903 in FIG. 49 and M isthe magnification of lens 4904 between the back focal plane of lens 4903(source block) and the detector array, which is in an image plane ofsaid back focal plane. By inspection of these equations, the dimensionof the scattering distribution is inversely proportional to the particledimension along the direction parallel to direction of the dimensionmeasurement. The 2-dimensional scattering distribution is measured by a2-dimensional detector array, such as a CCD array. For a rectangularparticle, use known image processing methods to determine the majoraxes, minor axes and orientation (a in FIG. 105) of the scatteringpattern and then measure the width and length of the pattern at thefirst zeros (xo and yo) in the scattering distribution in the directionsof the major and minor axes. Then the particle dimensions are given by:

A=w1/(sin(arctan(xo/F))

B=w1/(sin(arctan(yo/F))

These equations describe the process for determining particle shape fora randomly oriented rectangular particle where we have assumed that theparticle is much smaller than the uniform intensity portion of thesource beam. Other equations, which model scatter from non-uniformillumination, must be used when these conditions are not satisfied.Other parameters (such as the point in the scatter distribution which is50% down from the peak) which describe the width and length of thescattering pattern can be used instead of xo and yo, but with differentequations for A and B. In general, the corresponding particle dimensionscan be determined from these parameters, using appropriate scatteringmodels which describe the scattering pattern based upon the effects ofparticle size, shape, particle composition and the fact that thescattering pattern was integrated while the particle passed through alight source spot of varying intensity and phase. This analysis forrectangular particles is one example for rectangular particles. Themodel for each particle shape (polygon, ellipsoid, cube, etc.) must becomputed from scattering theory for nonspherical particles usingalgorithms such as T-matrix method.

The hardware concept is shown in FIG. 49. This system is very similar tothose shown previously in this disclosure in FIG. 32. Pinhole 4911removes high angle background from the light source and lens 4902collimates the source for passage through the sample cell through whichthe particle dispersion flows. The light source, lenses 4901 and 4902,and pinhole 4911 could be replaced by a nearly collimated light beamsuch as a laser beam. Two optical systems view the particles. The2-dimensional array #1 measures the scattering distribution from eachparticle and 2-dimensional array #2 measures the image of each particle.Array #1 is used to measure the dimensions of a smaller particle andarray #2 measures the larger particles where the array pixel size canprovide sufficient size resolution as a percentage of particle dimensionfor accurate dimension measurement. The scattering pattern from theparticle is formed in the back focal plane of lens 4903 and this scatterpattern is imaged onto array #1 by lens 4904. A small block is placed inthe back focal plane of lens 4903 to block the unscattered focused lightfrom the light source so that it will not reach array #1. The sourcelight would saturate some pixels on that array and these pixels maybloom or crosstalk into adjacent pixels where very low level scatteredlight is being measured. The source block could also be replaced by anannular spatial mask (as shown previously) to measure scatter only overa certain range of scattering angles. Aperture 4921 (also see FIG. 50)is placed in an image plane of the sample cell to define a restrictedregion of the beam where particles will be counted. This region isconfined to where the intensity profile of the source beam hassufficient uniformity. If this region of confinement is not required andaccess to the surface of the CCD is available (windowless CCD array)then lens 4904 and aperture 4921 could be removed and the CCD arraycould be placed in the back focal plane of lens 4903, directly behindthe source block. The beam diameter and lens diameters are not drawn toscale. They are drawn to display the details of beam divergence andconjugate planes. Lenses 4942B, 4903 and 4943B might actually be muchlarger than the beam diameter to collect scatter over a large range ofscattering angles.

A second similar optical system (system B which contains lenses 4941B,4942B, 4943B, 4944B etc.) is placed upstream of the particle flow fromthe system (the main system which contains lenses 4901, 4902, 4903,4904, etc.) described above (see FIG. 49). This system B reduces many ofthe problems associated with CCD arrays which are mentioned above.System B measures the scattered light from each particle before itpasses through the main system described above. This scattered lightlevel determines the particle size and predicts the signal levels whichwill be seen from that particle when it passes though the main system.These predicted levels provide the ability for the system to eitheradjust the intensity of light source 4951 or the gain of array 4952 tonearly fill the range of the analog to digital converter which digitizesthe scattering pattern data from array 4952 and to improve signal tonoise. The analog to digital converter and array pixel dynamic signalrange is not sufficient to measure scattered light levels from particlesover a large range of sizes. For example, the lowest scatter anglesignal will change over 8 orders of magnitude for particles between 1and 100 microns. However, the dynamic range of most CCD arrays isbetween 200 and 1000. Therefore, by adjusting the source intensity sothat the maximum pixel value on array 4952 will be just below saturationfor each particle, the optimum signal to noise will be obtained. Thetime of the pulse from the upper system B will predict when eachparticle will pass through the main system, using the flow velocity ofthe dispersion through the cell. So the array only needs to integrateduring the particle's passage through the source beam. This minimizesthe integration time and shot noise of array 4952. This timing couldalso be used to pulse the laser when the particle is in the center ofthe source beam for imaging by array 4953 to freeze the particle motionduring the exposure. Also the predicted size from system B could be usedto choose only particles in a selected size range for shape measurement.Or some smaller particles could be passed without dimensionalmeasurement to increase the statistical count of larger particlesrelative to the smaller particles to improve the counting statistics forthe larger particles which are usually at lower number concentrationthan the smaller particles. But the size distribution could then becorrected by the total count distribution from the upper system B, whilethe particle shape count distribution is determined from the fewerparticles counted by the main system. The size of the scattering patterncould also be predicted by system B so that an appropriate sub-array ofarray 4952 would be digitized and analyzed to save digitization time.The size prediction can also determine which array (4952, 4953 or both)will be digitized to determine the particle dimensions. The upstreamsystem B particle counts could also be used to determine coincidencecounting while the particle concentration is being adjusted. Many ofthese techniques are used to reduce the digitization load on the analogto digital converter, if required.

Lens 4944B acts as a field lens to collect scattered light and place thescatter detector in the image plane of the sample cell. This detectorcould be a single element detector which simply measures the all of thescattered light over a large range of scattering angles. However, thissingle detector measurement could be complicated by the variation oflight intensity across the source beam. The use of a three detectormulti-element detector (see FIG. 50) could be used in this image planeof the sample cell. Then only particles which produce signal primarilyon the center detector (of the three detector set) would be accepted forcounting. This particle selection could be based upon the ratios betweenthe signal from the center detector element with the correspondingsignal from either of the outer elements, as described previously inFIG. 37. The particle will be counted only if these two ratios are bothabove some threshold. If a large single detector is used instead of themulti-element detector, lens 4944B could be removed and the detectorcould be placed directly behind the source block if it is large enoughto collect all of the scattered flux. Otherwise a lens should be used tocollect the scattered light and focus it onto the detector.

If the upstream system B is not used, the CCD array scans of eachscatter pattern should be made over multiple long periods (manyindividual particles counted per period with one array scan perparticle) where the light source intensity or detector pixel gain ischosen to be different during each period. In this way particles indifferent size and scattering efficiency ranges will be counted at theappropriate source irradiance or detector pixel gain to provide optimalsignal to noise. So during each period, some particles may saturate thedetectors and other particles may not be measured due to low scatteringsignals. Only particles whose scattering efficiency can produce signalswithin the dynamic range of the array for that chosen light source levelor gain will be measured during that period. So by using a differentsource level or gain during each period, different size ranges aremeasured separately, but with optimal signal to noise for each sizerange. The counting distributions from each period are then combined tocreate the entire size and shape distribution. This method will requirelonger total measurement time to accumulate sufficient particle countsto obtain good accuracy because some particles will be passed withoutcounting. The use of system B to predict the optimal light source levelor pixel gain provides the optimum result and highest counts per second.These methods can also be used to mitigate detector array dynamic rangeproblems in any other system in this application.

The main system counting capability, as shown in FIG. 49, could be addedto any diffraction ensemble system by using the scatter collection lens(lens 5303 in FIG. 53) in the ensemble system to act as lens 4903 in thecounting system in FIG. 49. The light path after the ensemble systemscatter collection lens (the lens forming the scatter pattern) would bepartially diverted, by a beamsplitter, to a detection system as shown inFIG. 49 after lens 4903. This detection system could be any appropriatevariation of the detection system (with or without array 4953 and itsbeamsplitter as shown in FIG. 49 for example). Also if source regionconfinement (as discussed above) is not required and access to thesurface of the CCD is available (windowless CCD array) then lens 4904and aperture 4921 could be removed and the CCD array could be placed inthe back focal plane of lens 4903, behind the source block. System Bcould also be added to the ensemble scattering system, but withsignificant added expense.

Linear CCD arrays do not have sufficient dynamic spatial range toaccurately measure scatter pattern profiles from particles over a largerange of particle size. For example, for a million pixel array, thedimensions are 1000 by 1000 pixels. If at least 10 pixel values areneeded to be measured across the scatter profile to determine thedimension in each direction, then 1000 pixels will only cover 2 ordersof magnitude in size. This size range can be increased to 4 orders ofmagnitude by using two arrays with different angular scales. FIG. 51shows a system similar to that shown in FIG. 49, but with an additionalscatter detection array (2-dimensional array 5153). Arrays 5152 and 5153are in the back focal planes of lens 5104 and lens 5105, respectively.Lens 5105 has a much longer focal length than lens 5104, so that eachpixel in array 5152 covers a proportionately larger scattering angleinterval. As each particle passes through system B, the particle size isestimated to determine which array (5152 of 5153) should be scanned anddigitized. Array 5152 should be used for small particles which scatterover large angles and Array 5153 should be used for larger particles.The use of two arrays with different angular scales provides much higherparticle count rates. For example, for 2 orders of size magnitude with asingle array, 1 million pixels must be digitized (1000 by 1000 withminimum of 10 pixels for the largest particle). However, if two smaller100 by 100 pixel arrays were used for array 5152 and array 5153 and thefocal length for lens 5105 was 10 times longer than the focal length oflens 5104. Then these two 10,000 pixel arrays could cover 2 orders ofmagnitude in size, equivalent to that of the single 1 million pixelarray; but only a maximum of 10,000 pixels must be digitized for eachparticle by using the size estimate from system B to determine whicharray to digitize. This design provides a factor of 100 increase in theparticle count rate. This rate could be further increased by onlydigitizing the minimum subarray needed to measure each particle, basedupon the size prediction provided by system B. Also, FIG. 51 shows theuse of separate apertures (aperture 5121 and aperture 5122) which havedifferent size openings. A smaller opening is used for the smallerparticle detector array to reduce the scatter volume and reduce theprobability of coincidence counting. Also detector arrays 5152 and 5153could both be digitized for each particle, without any array selectionbased upon signals from system B. The scattering data from both arrayswould be combined to determine the size of each particle.

FIG. 49 a shows an analog version of the laser power control by systemB. The peak detector receives the total signal, through port E, from thedetector elements of the multi-element detector behind lens B. Thisdetector could also be a single element detector if particle positiondetection is not used to define a small interaction volume, as describedpreviously. When the peak detector breaks a threshold, it starts (byport C) the integration of the detector arrays in the main system afteran appropriate delay, accounting for the distance between the systemsand the flow velocity. When the integration is finished, the array(through port D) resets the peak detector to start to look for the nextparticle. The peak value held by the peak detector is input (input B) toan analog ratiometer with an adjustable reference voltage input A, whichcan be set to adjust the laser power, and hence the scatter signal, tonearly fill the analog to digital converter of the detector array in themain system. In this way, the light source intensity is rapidly changedto always nearly fill the range of the A/D converter for particles overa large range of size and scattered light signal. The value A/B couldalso be used to set the gain on the detector arrays, but this willprobably not have sufficient speed. This entire process could also bereplaced by its digital equivalents, but with much slower response andlower count rate.

One note must be made about diagrams in this application. The size ofthe scatter collection lens, (i.e. lens 4903 in FIGS. 49 and 50) is notshown in proper size relationship to the source beam in order to showmore detail of the source beam and different focal planes in the design.This is true for all scatter collection lenses shown in this disclosure.In all cases we assume that the scatter collection lens is of sufficientdiameter to collect scattered light from the particles over all of thescattering angles being measured. In some cases this may require thelens diameter to be much larger than the diameter of the source beam.

This application also describes concepts for combining three differentparticle size measurement modalities: particle counting, ensemblescattering measurements, and dynamic light scattering. In this case,particle counting is used for the largest particles (>100 microns) whichhave the largest scattering signals and lowest particle concentrationand least coincidence counts. The angular scatter distribution from aparticle ensemble is used to determine particle size in the mid-sizedrange (0.5 to 100 microns). And dynamic light scattering is used tomeasure particles below 0.5 micron diameter. These defined size rangebreak points, 0.5 and 100 microns, are approximate. These methods willwork over a large range of particle size break points because the usefulsize ranges of these three techniques have substantial overlap:

Single beam large particle counting (depends on the source beam size) 10to 3000 micronsParticle ensemble 0.1 to 1000 micronsDynamic light scattering 0.001 to 2 microns

One problem that can be solved by particle counting is the problem ofbackground drift in ensemble scattering systems which measure largeparticles at low scattering angles. An ensemble scattering systemmeasures the angular distribution of scattered light from a group ofparticles instead of a single particle at one time. FIG. 53 shows anensemble scattering system (except for detectors B1 and B2 whichillustrate additional detectors) which illuminates the particles with anearly collimated light beam and collects light scattered from manyparticles in the dispersion which flow through the sample cell. Thelight source is focused through pinhole 5311, which removes high angledefects in the beam intensity profile. Lens 5302 collimates the beamthrough the sample cell. Lens 5303 collects scattered light from theparticles in the sample cell and focuses that light onto a detectorarray in the back focal plane of lens 5303. An example of the detectorarray design is shown in FIG. 54. The optical system measures scatteredlight in certain angular ranges which are defined by the set of detectorelements. The elements can have different shapes, but in general thescattering angle range for each element is determined by the radius fromthe optical axis in the back focal plane of lens 5303. In some cases,the detector array will have a central detector, D0, which captures thelight from the source beam. Detectors D1, D2, etc. collect variousangular ranges of scattered light. Each detector element is connected toits own separate electronic integrator, which is connected to amultiplexing circuit and analog to digital converter (ADC) as shown inFIG. 54 for detectors D3, D4, D5, and D6. This multiplexer sequentiallysamples each of the integrators which may integrate while many particlespass through the beam. So particle pulses cannot be measured in theensemble system. All detector elements are connected to the multiplexerthrough integrators in a particle ensemble measuring system. FIG. 54shows the modification, for detector elements D0, D1 and D2, proposed bythis invention.

The detector elements which measure the low angle scatter (for exampleD1 and D2) usually see a very large scattering background withoutparticles in the sample cell. This background is due to debris onoptical surfaces or poor laser beam quality. Mechanical drift of theoptics can cause this background light to vary with time. Usually thedetector array is scanned with only clean dispersant in the sample cellto produce background scatter readings which are then subtracted fromthe subsequent readings of the actual particle dispersion. So first thedetector integrators are integrated and scanned without any particles inthe sample cell and then particles are added to the dispersion and thedetector integrators are integrated and scanned a second time. The firstbackground scan data is subtracted from this second scan for eachdetector element in the array. However, if the actual background driftsbetween the two scans, a true particle scattering distribution will notbe produced by the difference between these two scans.

A much better solution is to connect each of the detector elements, forthe lowest angle scatter, to individual analog to digital converters, orpeak detectors as disclosed before by this inventor. Then these signalscould be analyzed by many of the counting methods which were disclosedby this inventor. This would essentially produce an ensemble/countinghybrid instrument which would produce counting distributions for thelarge particles at low scattering angles and deconvolved particle sizedistributions from the long time integrated detector elements (ensemblemeasurement) at higher scattering angles for the smaller particles.These distributions can be converted to a common format (such asparticle volume vs. size or particle count vs. size) and combined intoone distribution. The advantage is that the frequency range for theparticle pulses is much higher than the frequencies of the backgrounddrift. And so these pulses can be measured accurately by subtracting thelocal signal baseline (under the pulse), determined from interpolationof the signals on the leading and trailing edge of each pulse, using thedigitized signal samples. At very low scattering angles, the scatteringsignal drops off by at least the fourth power of particle diameter.Therefore larger particle pulses will stand out from the signals frommany smaller particles which may be in the beam at any instant of time.Also the number concentration of larger particle will be low and providefor true single particle counting.

The smallest particles are measured using dynamic light scattering asshown in FIG. 55. A fiber optic dynamic light scattering system, asdescribed previously by the inventor, is inserted into the tubingthrough which the particle dispersion flows. This fiber opticinterferometer measures the Doppler optical spectral broadening of thescattered light caused by Brownian motion of the particles. The sizerange is determined from this spectral broadening by techniquesdescribed previously by this inventor. The counting and ensemblescattering measurements are made with dispersion flowing through thesystem. This flow would be turned off during the collection of dynamiclight scattering signals to avoid Doppler shifts in the scatteringspectrum due to particle motion. The particle size distributionsdetermined from each of the three systems: counting, ensemble, anddynamic light scattering are combined into one particle sizedistribution which covers a very large size range.

The particle counting uses the lowest angle zones (D1, D2, etc.) and thebeam measuring zone (D0) of the detector array (an example of a detectorarray is shown in FIG. 54). Each of these detector elements areconnected to a separate ADC to measure the scattering pulse in D1, D2,etc. and the signal drop on detector D0 as each particle passes throughthe interaction volume where the beam illuminates and from which thescattering detectors can receive scattered light from the particles. Oneproblem is that the amount of scattered light is nearly proportional tothe illumination intensity of the source on the particle. Therefore asparticles pass through different regions in the beam they may producedifferent pulse heights. FIG. 56 shows a Gaussian intensity distributionwhich might be characteristic of the cross-section of a laser beam.Since the probability of particle passing through this beam at anyposition is approximately the same, we can generate the count vs. pulseamplitude distribution in FIG. 57, which shows the count distributionfor large number of identical particles (also shown in FIGS. 10 and 10a). Notice that most of the particles pass through the low intensityportions of the intensity distribution and many particles also passthrough the uniform intensity region which is close to the peak of theintensity distribution, with a region of lower count level in between.This broad count response to a group of mono-sized particles willprevent accurate determination of complicated particle sizedistributions, because the pulse heights may be ambiguous for varioussized particles. For example, a large particle passing through the lowerintensity region can produce a pulse which is very similar to that froma smaller particle passing through the higher intensity region. Theregion of the intensity distribution which can produce scattered lightinto the detectors must be truncated by apertures in the source optics(aperture 5201 in FIG. 52) or in the detection optics (aperture 5202 inFIG. 52). Either of these apertures can create a “region passed byaperture” as indicated in FIGS. 56 and 57. By using either or bothapertures, only the upper region of the count vs. pulse amplitudedistribution will be seen for many particles of a single particle size.This truncation by aperture can be used in any of the systems describedin this document to reduce the broadening of the particle count peaksdue to intensity variations of the source. Any residual broadening isthen removed by algorithms such as deconvolution.

Another method for eliminating this intensity distribution effect is touse ratios of detector signals. This works particularly well when manyof the detectors have scatter signals. However, for very largeparticles, only scattering detector D1 will see a high scatter signalwith high signal to noise. So for very large particles, the aperturesdescribed previously may be required to use the absolute scatter fromD1. Another solution is to use the ratio of the drop in D0 (signal S0)and the increase in D1 (signal S1) due to scatter as shown in FIG. 58A.As a particle passes through the beam D0 will decrease by approximatelythe total scattered light and D1 will increase by only the amount oflight scattered into the angular range defined by that detector. Thedrop in D0 can be determined by subtracting the minimum of drop in S0from the baseline A0 to produce a positive pulse A0-S0 as shown in FIG.58B. As shown in FIG. 59, the ratio of either the integral or the peakvalue of the corresponding pulses from these two signals can be used todetermine the size of the counted particle for the largest sizeparticles which have insufficient scatter signal in D2 to produce aratio between S1 and S2. As long as D2 has sufficient scatter signal andD2 captures a portion of the primary lobe of the angular scatterdistribution, the ratio between S1 and S2 will produce more accurateindication of size, than a ratio between S0 and S1. The primary lobe ofthe scattering distribution is the portion of the distribution from zeroscattering angle up to the scattering angle where the size informationbecomes more ambiguous and particle composition dependent. Usually thishappens when the scatter function first drops below 20% of the zeroangle (maximum) value of the function. For a certain range of smallerparticles, the ratio between S1 and S3 (if D3 were connected to an A/Das D2) may have higher sensitivity to particle size than the ratio of S1to S2. For smaller particle diameters, ratios to larger angle scattersignals will provide better sensitivity. A0-S0, S1, etc. could be alsobe analyzed using the other methods described in this document.

The signal ratio technique is needed when the “region passed byaperture” in FIGS. 56 and 57 is too large such that mono-sized particlesproduce pulse peaks over a large amplitude range. For example, if noaperture were used, then mono-sized particles will produce the entirecount distribution shown in FIG. 57, with ambiguity between smallparticles passing through the center of the Gaussian intensitydistribution and large particles passing through the tail of thedistribution. In cases where the “region passed by aperture” is toolarge, the use of signal ratios (as described previously) is required toreduce the effect of the intensity variation (because the intensityvariation drops out of the ratio, approximately). If the sourceintensity distribution can be made more uniform by use of an aperture(aperture 5201 of FIG. 52) or by use of a non-coherent source, or if theviewing aperture (aperture 5202 in FIG. 52) of the detector only views arestricted region where the source intensity is more uniform, thenscattering amplitude can be used directly to determine size as shown inFIGS. 60 and 61, using the methods described for FIGS. 26, 27, 27 a, and28. This may have some advantages when only one detector has sufficientsignal and two signals are not available to create a ratio. Also theabsolute signal amplitude information, which is lost in the ratiocalculation, can be useful in determining the particle composition andin eliminating pulses which are due to noise, as will be described inFIG. 61. FIG. 57 shows a count vs. pulse amplitude response with a“region passed by aperture”. This count distribution in the “regionpassed by aperture” is plotted on a logarithmic scale of S (or pulsepeak or integral) for two different particle sizes, in FIG. 60. Eachfunction has an upper and lower limit in log(S). Notice that, inlogarithmic S space, the two functions are shift invariant to particlediameter. The upper limit is due to particles which pass through thepeak of the source intensity distribution and the lower limit is fromthe edge of the truncated source intensity profile. So that the countper unit log(S) interval vs. log(S), Ns(log(S)), distribution fromparticles of the count vs. particle diameter distribution Nd(d) is theconvolution between the shift invariant function in FIG. 60, H(log(S),and the count vs. particle size distribution, Nd(d) as describedpreviously for FIGS. 26, 27, 27 a and 28:

Ns(log(S))=Nd(d)ΘH(log(S))

This equation is easily inverted by using iterative deconvolution todetermine Nd(d) by using H(log(S)) to deconvolve Ns(log(S)). In somecases, for example when S=A0-S0, the form of this equation may not be aconvolution and a more generalized matrix equation must be solved.

Ns(log(S))=H(log(S))*Nd(d)

Where H is the matrix and Nd(d) is a vector of the actual counts perunit size interval. Each column of matrix H is the measured count perunit log(S) interval vs. log(S) response to a particle of sizecorresponding to the element in Nd(d) which multiplies times it in thematrix multiply ‘*’. This matrix equation can be solved for Nd(d), givenNs(log(S)) and H(log(S)). This equation will also hold for the casewhere the functions of log(S) are replaced by other functions of S.

FIG. 61 shows a scatter plot of the counted data points in the twodimensional space, where the two dimensions are the logarithm of pulseamplitude or pulse integral for two different signals A or B. Forexample SA and SB could be S1 and S2, or A0-S0 and S1. Two squares areshown which encompass the approximate region where counts from particlescould occur for each of two particle diameters. SAU and SAL refer to theupper and lower limits of the signal, respectively, as shown in FIG. 60.The lower limit, SAL, is determined by the cutoff of the aperture on thesource intensity profile. The upper limit, SAU, is the maximum signalvalue when the particle passes through the peak of the source intensityprofile. In the two dimensional space, shown in FIG. 61, points areshown where the particle passes through the intensity peak,[log(SBU),log(SAU)], and where the particle passes through the edge ofthe intensity profile, [log(SBL),log(SAL)], where the intensity islowest. As particle size changes, this square region will move along acurve which describes the scatter for particles of a certaincomposition, as shown in FIG. 62. The moving square will define aregion, between the two lines which pass through the edges of thesquare. Real particles can only produce points within this region.Points outside this region can be rejected as noise points or artifactsignals. This two dimensional count profile can be deconvolved using2-dimensional image deconvolution techniques (as described previously),because each square defines the outline of the two dimensional impulseresponse in Log(S) space. The two dimensional count profile is theconcentration (counted points per unit area of log(SA) and log(SB) plot2-dimensional space) of counted points at each coordinate in the log(SA)and log(SB) space. This count concentration could be plotted as the Zdimension of a 3-dimensional plot where the X and Y dimensions arelog(SA) and log(SB), respectively. The two dimensional impulse functionplotted in the Z dimension of this 3-dimensional space is determinedfrom the product of functions as shown in FIG. 60, one along each of thelog(SA) and log(SB) axes of FIGS. 61 and 62. If absolute signal valuesare used instead of signal ratios, the single size response will bebroader in the multi-dimensional space and the deconvolution (or generalinversion if not a convolution) problem will be more ill-conditioned.However, this can be the best choice for very small particles where theabsolute signals will have much greater particle size sensitivity thanthe signal ratios. FIG. 39 shows a hybrid 2-dimensional plot of Log(S1)vs. S1/S2 which combines these two methods. Three data points for 0.1,0.5, and 0.8 micron diameter particles are shown to illustrate sizedependence. The S1/S2 axis shows more sensitivity to larger particlesand the Log(S1) axis shows more sensitivity to smaller particles. Thishybrid plot is a good compromise over a large size range. All of thetechniques for multi-dimensional analysis, described previously, applyto this case. In this case, the 2 dimensional space would be deconvolvedprimarily in the Log(S1) direction only, where the function broadeningdue to source intensity variation occurs. Very little broadening willoccur in the S1/S2 function dimension due to the ratio correction, butthe single particle response should include any broadening in the S1/S2direction also. If deconvolution is too slow, another technique may beused to eliminate broadening in the Log(S1) direction. After the outlierevents are eliminated and the Cg function is created from the raw countpoints on the Log(S1): S1/S2 plane, as described for FIG. 26, slices ofthat Cg function can be made parallel to the Log(S1) axis at variousvalues of S1/S2. Each slice will provide a function of Log(S1) with thebroadening due to Log(S1) at that value of S1/S2. Each slice functionwill look like one of the functions shown in FIG. 60. Since thisfunction is the known function from theoretical or empiricalmeasurements of single sized particles, a fitting algorithm can veryquickly determine the position of this function on the Log(S1) axis.Each function in each slice is then replaced by a single point at aconsistent location (center or upper edge SAU in FIG. 60, etc.) of thefunction in each slice, with a value equal to the total particlescounted in that slice. Then the broad distribution of points in Cgbecomes a single line in Log(S1): (S1/S2) space, as in the deconvolutioncase. In either case, the count distribution function along this singleline has one to one correspondence to particle size. Therefore, thecounts at each point along this line represent the number of particleswith a size corresponding to that point. This line data can also beanalyzed by methods described elsewhere in this application to producethe particle count vs. size distribution. These multi-dimensional viewsand the previously described methods apply to all combinations ofsignals (S1, S2, etc.), Log(signals) (Log(S1), Log(S2), etc), Ratios ofsignals (S2/S1, S3/S1, etc), and/or any combinations of these (S1/S2 andLog(S1), etc.). Where the signals S1, S2, etc. are functions of themeasured scatter signal (such as peak value, integral, value at acertain time during the pulse, product of two scatter signals, etc.)

FIGS. 10 a, 26, 27, 27 a, 28, 60, 61, 62 all describe different aspectsof correction for broadening of the count distribution vs. signalresponse for a single sized particle. FIG. 10 a describes the particlecount distribution vs. scattering signal from single sized particles ina source spot with a Gaussian intensity profile. This figure shows theeffects of spatial truncation (FIG. 1A for example) of the beam, beforethe sample cell area, using an aperture in a plane conjugate to theplane of the particles. More particles will be counted in the regions oflow slope in the intensity distribution, explaining the rise at each endof the count distribution in FIG. 10 a. FIGS. 26 through 28 show thegeneral form of the 2-dimensional count distribution, showing that thecount distribution from a group of single sized particles would beconcentrated in region with shape similar to an ellipse. Ideally thisellipse impulse response would collapse to a line segment which isequivalent to the major axis of each ellipse in these figures, if theonly source of count distribution broadening is the intensity profile ofthe source. The projection of the count distribution along this line,onto the Log(S2) and Log(S1) axes will look like the function in FIG. 10a. In this case, we obtain FIGS. 60, 61, and 62. FIG. 60 shows the sameresponse as FIG. 10 a, with truncation of the source beam at a very highintensity level to eliminate the long intensity tails. The distributionsin FIG. 60 (for Log(S)) are for ideal truncation, the actual functionswill look more like the “with aperture (aberrated)” case in FIG. 10 a(but for the Log(S) instead of S case). FIGS. 61 and 62 show rectanglesindicating the axes of these projections and the extent of the functionsin FIG. 60, in 2-dimensions. This 2-dimensional response to a singleparticle is the impulse response for the deconvolution of the2-dimensional count distribution. Each of the 1-dimensionaldistributions of count per unit Log(S1) vs. Log(S1) and count per unitLog(S2) vs. Log(S2) could each be deconvolved separately using theimpulse response similar to that shown in FIG. 10 a or FIG. 60. Then theresults from these two deconvolved functions would be combined betweencorresponding data points to create a 2-dimensional plot withoutbroadening. Also a single 1-dimensional distribution (signal vs.particle size) could also be deconvolved to use only absolute scatteringsignal as the particle size indicator. However, the 2-dimensionaldeconvolution, using existing image deconvolution algorithms, shouldproduce better results but with longer computation time. Since thisdeconvolution is only done once, after all of the particles are counted,the long computation time may not be an issue. The 2-dimensionalresponse function can be determined by measuring the 2-dimensional countdistribution from a large number of single sized particles, which willrandomly pass through paths covering the entire source spot. If thesignal threshold in FIG. 10 a is set too high, the bottom portion of theresponse from the smallest particle may be cut off, requiring a matrixmodel and inversion instead of a convolution model and deconvolution.The best solution is to insure that the signal detection threshold islower than lowest end of the count response from the smallest particle.If binary optic of other methods are used to create a flat top intensitydistribution for the source spot, then the line segment will collapseclose to a small spot in 2-dimensional space and the deconvolution willbe very well conditioned. A longer line segment or width of the“ellipse” of the single size response will create an ill-conditionedinversion problem, producing larger errors in the resulting sizedistribution. The 1-dimensional or 2-dimensional particle count per unitlog(S) distribution, after deconvolution, will have a one to onecorrespondence to size, because each particle diameter will have acorresponding location in S1,S2 space or Log(S1),Log(S2) space. Thecounts per unit S1 and S2 interval can be converted to counts perparticle size interval based upon this one to one correspondence. Alsoeach signal could be separately analyzed as signal vs. size parameter toproduce a size distribution for each signal in the size range where thatsignal has the best size sensitivity or monotonicity. Then thesemultiple size distributions are combined by concatenation with overlapregions as shown previously.

These multi-dimensional views and the previously described methods applyto all combinations of signals (S1, S2, etc.), Log(signals) (Log(S1),Log(S2), etc), Ratios of signals (S2/S1, S3/S1, etc), and/or anycombinations of these (S1/S2 and Log(S1), etc.). Where the signals S1,S2, etc. are functions of the measured scatter signal (such as peakvalue, integral, value at a certain time during the pulse, product oftwo scatter signals, etc.) These signals can include: individual scattersignal peak heights (the individual peak of each signal withoutsimultaneous detection), signals values measured simultaneously at thetime when a chosen detector is at peak value, scatter signal pulsewidths (time), pulse shape, time delay between pulses from differentdetectors, pulse frequency spectrum parameters (pulse structure such asheterodyne oscillation frequency), integrals of pulses, product of twosignals from two different detectors (correlation relationship),integral of the product of two signal pulses from different detectors,ratio of any two of the parameters in this list, logarithm of anyparameter in this list. The logarithm scale for the count distributionis particularly useful to remove broadening from spatial variations ofbeam intensity with deconvolution techniques, because then the countresponse is shift invariant to signal level. Also peak detection(simultaneous or individual) will also remove some broadening from thesingle size response to improve inversion or deconvolution results. Theabove parameters will create single particle size response functionswhich can be used to remove broadening of those parameters in themulti-dimensional space, through deconvolution or solution ofsimultaneous equations. These parameters can also be used to createrules for rejection of signal events which are not particles or do nothave sufficient signal to noise.

The previous concept for ensemble particle systems uses particlecounting to eliminate the particle size errors caused by backgrounddrift in the angular scattering signals, because the frequency contentof the counted pulses is much higher than the background drift, and sothe pulses can be detected by methods described previously by thisinventor, without being effected by background drift. The local baselineis easily subtracted from each pulse because the background drift isnegligible during the period of the pulse. However, this advantage canalso be used with the integrators as shown in FIG. 63. The slowlyvarying baseline can be removed by high pass analog electronic filterswith a cutoff frequency between the lowest frequency of the particlescatter pulse spectrum and the highest frequency of the background driftspectrum. The input to each of the integrators which follow each highpass filter are the particle scatter pulses, without background which isattenuated by the filter. These pulses can be integrated and multiplexedinto the same analog to digital converter as the higher scattering anglesignals, which do not need the highpass filtering to remove the baselinedrift. These integrators integrate over an extended period where manyparticles pass through the beam. In the case of smaller particles, theremay be many particles in the beam at any instant in time. However, sincethe scatter signal from larger particles is much larger than that forsmaller particles and with many smaller particles in the beam, thesesmaller particle signals will have very low fluctuations relative to thediscrete pulses from the larger particles. So this high pass filteringwill select the larger particles where the scatter signal fluctuationsare large. This measurement could also be made with an RMS (root meansquared) module which only detects the higher frequency portion of thescatter signal for the lower angle detectors. All of these integratedsignals, from low and high angle scatter detectors, are then inverted bytechniques such as deconvolution. The detector signals could also bedigitized directly; and the filtering and integration steps could bedone digitally. However, the optical scatter model for the deconvolutionmust include the loss of the small particle contribution to thesefiltered signals, because as the number of particles in the beamincreases, the higher frequency components will be attenuated due tooverlap of pulses. Given this attenuation process and the fact thatsignals at the lowest scattering angles scale as the fourth power ofparticle diameter, the smaller particle signals should not besignificant in these filtered low angle signals. The correction to themodel is very minor; essentially the small particle contribution tothese filtered detector signals can be assumed to be small in thescattering model.

These methods do not assume any particular number of lower angle zones.For example, D0, D1, D2, and D3 could be handled with the techniquesabove. Essentially, any detectors with background drift problems shouldbe handled with these methods.

Normally all of the ADC scans of the multiplexer output are summedtogether and this sum is then inverted to produce the particle sizedistribution. But due to the large difference in scattering efficiencybetween large and small particles, smaller particles can be lost in thescatter signal of larger ones in this sum. This problem can be mitigatedby shortening the integration time for each multiplexer scan and ADCcycle to be shorter than the period between pulses from the largeparticles. Then each multiplexer scan and subsequent digitization can bestored in memory and compared to each other for scattering angledistribution. ADC scans of similar scattering angular distribution shapeare summed together and inverted separately to produce multiple particlesize distributions. Then these resulting particle size distributions aresummed together, each weighted by the amount of total integration timeof its summed ADC scans. In this way, scans which contain largerparticles will be summed together and inverted to produce the largeparticle size portion of the size distribution and scans which containonly smaller particles will be summed together and inverted to producethe small particle size portion of the size distribution, without errorscaused by the presence of higher angle scatter from larger particles.

Another method to measure larger particles is to place a sinusoidaltarget in an image plane of the sample cell on front of a scatterdetector as described previously by this inventor. The dispersant flowcould be turned off and then the particle settling velocity could bemeasured by the modulation frequency of the scatter signal fromindividual particles settling through the source beam. The hydrodynamicdiameter of each particle can then be determined from the particledensity, and dispersant density and viscosity.

Finally the three size distributions from dynamic light scattering,ensemble scattering and counting are combined to produce one singledistribution over entire size range of the instrument by scaling eachsize distribution to the adjacent distribution, using overlappingportions of the distribution. Then segments of each distribution can beconcatenated together to produce the complete size distribution, withblending between adjacent distributions in a portion of each overlapregion. This method works well but it does not make most effective useof the information contained in the data from the three sizing methods.Each inversion process for each of the three techniques would benefitfrom size information produced by other techniques which produce sizeinformation in its size range. This problem may be better solved byinverting all three data sets together so that each of the three methodscan benefit from information generated by the others at each step duringthe iterative inversion process. For example, the logarithmic powerspectrum (dynamic light scattering), logarithmic angular scatteringdistribution and logarithmic count distribution could be concatenatedinto a single data vector and deconvolved using an impulse response oflikewise concatenated theoretical data. However, in order to produce asingle shift invariant function, the scale of the counting data must bechanged to produce a scale which is linear with particle size. Forexample, the pulse heights on an angular detector array will scalenearly as a power function of particle size, but the power spectrum andensemble angular scattering distributions shift along the log frequencyand log angle axes linearly with particle size. So a function of thepulse heights must be used from the count data to provide a countfunction which shifts by the same amount (linear with particle size) asthe dynamic light scattering and ensemble distributions. This functionmay vary depending upon the particle size range, but for low scatteringangles the pulse height would scale as the fourth power of the particlediameter, so that the log of the quarter power of the pulse heightsshould be concatenated into the data vector. This technique will workeven though the concatenated vectors are measured verses differentparameters (logarithm of frequency for dynamic light scattering,logarithm of scattering angle for ensemble scattering, and logarithm ofpulse height or integral for counting), simply because each functionwill shift by the same amount, in its own space, with change in particlediameter. And so the concatenation of the three vectors will produce asingle shift invariant function which can be inverted by powerfuldeconvolution techniques to determine the particle size distribution.This technique can also be used with any two of the measurement methods(for example: ensemble scattering and dynamic light scattering) toprovide particle size over smaller size ranges than the threemeasurement process. In the concatenated problem where this convolutionform is not realized, the problem can also be formulated as a matrixequation, where the function variables can be Log(x) or x (where x isthe variable frequency (dynamic light scattering), scattering angle(ensemble angular scattering) or S (the counting parameter)). Againthese functions can be concatenated into vectors and a matrix oftheoretical concatenated vectors. And this single matrix equation, whichcontains the dynamic light scatter, the ensemble scatter and the countdata, can be solved for the differential particle volume vs. sizedistribution, Vd, without being restricted to convolution relationshipsor the need for matching function shifts with particle size.

Fm=Ht*Vd

Where Fm is the vector of measured values which consist of threeconcatenated data sets (dynamic, angular, and counting). Ht is thetheoretical matrix, whose columns are the theoretical vectors which eachrepresent the theoretical Fm of the size corresponding to the value Vdwhich multiplies that column. This matrix equation can be solved for Vd,given Fm and Ht.

If the convolution form holds, then the equation becomes:

Fm=HimΣVd

Where Him is the Fm response at a single particle size and Θ is theconvolution operator. This equation can be solved for Vd, given Fm andHim.

Another way to accomplish this is to constrain the inversion process foreach technique (dynamic light scattering, ensemble scattering andcounting), to agree with size distribution results from the other twotechniques in size regions where those other techniques are moreaccurate. This can be accomplished by concatenating the constrainedportion of the distribution, Vc, onto the portion (Vk) which is beingsolved for by the inversion process during each iteration of theinversion. The concatenated portion is scaled relative to the solvedportion (AVc), at each iteration, by a parameter A which is also solvedfor in the inversion process during the previous iteration. This can bedone with different types of inversion methods (global search, Newton'smethod, Levenburg-Marquart, etc.) where the scaling parameter A issolved for as one additional unknown, along with the unknown values ofthe particle size distribution. This technique will work for anyprocesses where data is inverted and multiple techniques are combined toproduce a single result.

Fn=Hnm*Vn (matrix equation describing the scattering model)

Vn=Vk|AVc (concatenation of vectors Vk and AVc, n number of total valuesin Vn)

Solve for k values of Vk and constant A

Vn=Fn/Hnm (solution of the matrix equation by iterative techniques (nota literal division))

k≦n+1

Another hybrid combination is particle settling, ensemble scattering,and dynamic light scattering as shown in FIG. 64. As before, dynamiclight scattering probes a portion of the particle dispersion flowstream, with the flow turned off. The ensemble scattering system uses adetector array to measure the angular scattering distribution fromgroups of particles in the sample cell as the dispersion flows throughthe cell. A particle settling measurement is used for the largestparticles which have the highest settling velocities. The settling ismeasured by sensing the power spectrum of the scattered light as viewedthrough a set of sinusoidal or periodic masks, which are also referredto as a multi-frequency modulation transfer target. Some examples ofthese masks are shown in FIGS. 16, 65 and 66. The mask can be placedbetween lens 6402 and lens 6403 or on front of a group of detectors asshown in FIG. 64. The detector is placed in the back focal plane of lens6403, as shown previously by the inventor, to collect scattered light inseparate ranges of scattering angle. A portion of the scattered light issplit off by a beam splitter to an aperture in the focal plane of lens6403. This aperture can be an annular opening, which passes a certainrange of scattering angles (signal rises as particle passes through abright fringe), or a pinhole centered to pass only the focused spot ofthe source (signal drops as particle passes through a bright fringe) inthe back focal plane of lens 6403. Where the fringe is defined in thesample cell plane as an image of each highly transmitting line in themulti-frequency target. The light passing through the aperture, alsopasses through a periodic mask, as described previously, which is in aplane conjugate to the sample cell. This mask contains multiple regions,each with a different spatial frequency for the periodic absorption orreflection pattern. Behind each region in the mask is a separatedetector which collects the light which only passes through that region,as also shown in FIGS. 15 and 15 a for a different mask location. Asparticles pass through a region, the scattered light (for the annularaperture) or the attenuation (for the pinhole passing the source) of thebeam are modulated by the motion of the particle's image across theabsorption cycles of the mask. The particle dispersion flow pump isturned off and the particles are allowed to settle through the samplecell. The frequency of signal modulation for any particle isproportional to its settling velocity, which indicates the hydrodynamicsize of the particle, given the particle and dispersant densities andthe dispersant viscosity. The signal can be digitized and analyzed on anindividual particle basis to count and size individual particles bymeasuring the settling velocity of each particle. In this case zerocrossing measurement or Fourier transform of the signal segments foreach particle could be used. In the case where many particles are in thebeam at each instant, the power spectrum of the signal could be measuredover an extended time. This power spectrum would then be inverted toproduce the particle size distribution using a matrix model as describedpreviously. As identical particles pass though different focal planes(planes perpendicular to the optic axis) in the sample cell, the powerspectrum will change because the sharpness of the image of the mask willbe reduced as the particle moves farther from the image plane. Also ifthe source beam is focused into the sample cell, as shown previously,then the source intensity and the scatter signal will drop as theparticle passes farther from the best focus plane of the source. Theseeffects can be included in the counting system model which is invertedto produce the particle size. The H function (or H matrix) describedpreviously will contain columns which describe the count vs. signalfrequency from a group of identical particles, of the size correspondingto that matrix column, passing through every point in the sample cell.For the ensemble scattering system model, the H function (or H matrix)will contain columns which describe the integrated scatter signal vs.angle from a group of identical particles, of the size corresponding tothat matrix column, passing through every point in the sample cell.

The following list describes the various options for using scatteredlight to measure size. In each case, the following matrix equation mustbe solved to determine V from measurement of F:

F=H*V

This equation can be solved by many different methods. However, becausethis equation is usually ill-conditioned, the use of constraints on thevalues of V is recommended, using apriori knowledge. For example,constraining the particle count or particle volume vs. sizedistributions to be positive is very effective. In some cases, as shownpreviously by this inventor, changing the abscissa scale (for examplefrom linear to logarithmic) of F can produce a convolution relationshipbetween F and V, which can be inverted by very powerful deconvolutiontechniques.

F=HΘV

Particle Counting

1) Angular scatter or attenuation due to scatter:V=particle count per size interval vs. sizeF=count per signal amplitude interval vs. signal amplitude where signalamplitude is either pulse peak value, integral of the pulse, or otherfunction of these valuesH=matrix where each column is the F function for the particle sizecorresponding to that column

Response broadening mechanisms in the H matrix:

A) source intensity variation in x and y directions where particles canpass (broadening reduced by aperturing of the intensity distribution atan image plane of the sample cell or using diffractive or absorptiveoptic beam shapers and apodizers to provide a “flat top” intensitydistribution in the interaction volume)B) source intensity variation in z direction (broadening reduced bydouble pulse sensing and correlation, and detector aperture at imageplane of sample cell)C) Residual broadening of signal amplitudes and ratios of signals due todifferences in interaction volumes between different detectors.D) Passage of the particles through various portions of each detectorfield of view(broadening reduced by only counting particles which are detected by thedetector with the smallest interaction volume, which is totally includedin all of the other detector interaction volumes)E) Random orientation of non-spherical particles (broadening reduced byusing annular detector elements which collect scattered light equallyfrom all scattering planes.)F) Variation of signal due to presence of more than one particle in theinteraction volume at one time.(This broadening is reduced by measuring at low scattering angles sothat scatter is proportional to at least the fourth power of particlediameter or by reducing the particle concentration to avoid particlecoincidences)Advantages: high resolution and aerosol capabilityDisadvantages: counting statistic errors for low count2) Settling (hydrodynamic size)V=particle count per size interval vs. sizeF=count per signal frequency interval vs. signal frequency where signalfrequency is the frequency of the scatter signal segment for the countedparticleH=matrix where each column is the F function for the particle sizecorresponding to that column

Response broadening mechanisms in the H matrix:

Finite length of modulated signal segment from each particleBrownian motionVariation of signal frequency along z directionAdvantages: high size resolution, excellent detection of small particlesmixed with large particles, excellent measurement of low tails in thesize distributionDisadvantages: counting statistic errors for low count; and possibledifficulty measuring large particles in aerosols due to very highsettling velocities

Ensemble Scattering

1) Angular scatter or attenuation due to scatterV=particle volume per size interval vs. sizeF=scattered light flux per scattering angle interval vs. scatteringangleH=matrix where each column is the F function for the particle sizecorresponding to that column

Response broadening mechanisms in the H matrix:

The broad angular range of scatter from a single particle described byscattering theoryAdvantages: excellent size reproducibilityDisadvantages: low size resolution, poor detection of small particlesmixed with large particles, poor measurement of low tails in the sizedistribution.2) Settling (hydrodynamic particle size)V=particle volume per size interval vs. sizeF=scattered light detector current power per frequency interval vs.frequencyH=matrix where each column is the F function for the particle sizecorresponding to that column

Response broadening mechanisms in the H matrix:

Finite length of modulated signal segment from each particleBrownian motionVariation of signal frequency along z directionAdvantages: high size resolution, excellent detection of small particlesmixed with large particles, excellent measurement of low tails in thesize distributionDisadvantages: difficulty measuring large particles in aerosols due tovery high settling velocities

In some cases, the matrix equation must be replaced by a set ofnon-linear equations which are solved to determine the particle sizedistribution from a count distribution which contains broadening due toa mechanism listed above. A more generalized form for this equation isto use operator notation Q=O[W], where O is an operator which operateson W to produce Q. For example in the case of counting:

Nm(S)=O[Nt(S)]

Depending upon the type of broadening mechanism, O may includeoperations such as matrix operation, set of non-linear equations, orconvolution operator. The count distribution N(S) is the number ofevents with signal characteristic S between S-deltaS and S+deltaS as afunction of S. S can be any of the signal characteristics (such asscatter signal peak or integral) or functions (such as logarithm) ofthese signal characteristics. Let Nm(S) be the measured countdistribution which contains the broadening. And let Nt(S) be the countdistribution without broadening. In each case, the operator describesthe contribution to Nm(S) from an event of signal characteristic S. Thisoperator is produced by calculating the broadened N(s) response to alarge group of particles, with identical size and shape characteristics.This response is calculated for many values of particle characteristicsto produce a set of equations. The response can also be determinedempirically by measurement of a large number of particles with a narrowsize distribution. Multiple narrow sized samples are measured at variousmean sizes to produce the count response functions Nm(S) for thosesizes. Then the response functions at other sizes are produced byinterpolation between these measured cases, using theoretical behaviorto solve for the interpolated values. The operator 0 is created byfitting functions to these measured results or by the closed formequations from theory.

Another system for counting and sizing particles, using imaging, isshown in FIG. 67. There are two optical systems, using light source 6711and light source 6712. The source 6711 system measures larger particlesby direct imaging of the particles, flowing through the sample cell,onto 2-dimensional detector array 6721. The source 6712 system producesa cone shaped illuminating beam, using the source block on lens 6701B,which defines an illuminated focus volume in the particle dispersion.This focal volume is imaged by lens 6703B though the mirror andbeamsplitter onto the same 2-dimensional detector array 6721. The focalvolume is placed close to the sample cell window which is closest to the2-dimensional array. Before and after the focal point of the source 6712in the cell, the illumination beam is a hollow cone, which provides anun-illuminated volume through which lens 6703B can view the focal pointof source 6712 in the sample cell. The 2-dimensional array ismultiplexed between the two systems by sequentially turning on eithersource 6711 or source 6712. Each source is pulsed so as to onlyilluminate the flowing particles during a travel distance which is lessthan the required imaging resolution. Alternately, the flow can bestopped during the exposure to eliminate any smearing of the image.

The source 6711 system can take many forms. In FIG. 67, aperture 6731(in the back focal plane of lens 6703) blocks the scattered light andpasses the un-scattered light (approximately) so that particles willappear as dark on a bright background. In FIG. 68, aperture 6731 isreplaced by a light block which blocks the un-scattered light and passesthe scattered light (approximately) so that particles will appear asbright on a dark background. In FIG. 68, pinhole 6811 is used to removeany higher angle components of light source 6821 which could createbackground light which can pass around the light block. In either case,contiguous detector array pixel values, which are above some thresholdin FIG. 68 or below some threshold in FIG. 67, can be combined todetermine the total light extinction of the particle (in FIG. 67) or thelight scattered in the acceptance angle of lens 6803 in FIG. 68. Thesevalues can be used to determine the size of particles throughout thesize range, even for a particle whose image size is less than the sizeof single pixel, as described previously in this document for FIGS. 11and 14. However, for very small particles, many particle coincidencecounts may occur in the source 6821 system and the signal to noise maydrop below acceptable levels. So the smaller particles are measured bythe source 6821B system, which focuses the source to a higher irradiancein the sample cell and defines a much smaller interaction volume thanthe other system. The source block on lens 6801B creates a hollow coneof light, which is focused close to inner sample cell window wall whichis closest to the detector array. This is shown in more detail in FIG.69. Lens 6903B collects scattered light from the particles, with a fieldof view which falls inside of the hollow cone of light. Therefore, onlyparticles in the source focal volume will contribute to the scatteredlight and the image formed on the detector array. Since the focus isclose to the inner wall, few particles will block or rescatter lightwhich is scattered by particles in the focal volume. However, thismethod will produce good results for any location of the lens 6901Bfocus, as long as lens 6903B is focused to the same location. Alsoparticles in the extended illuminated portions of the hollow cone cannotcontribute scatter to lens 6903B due to the limited acceptance cone ofthis lens. The optical magnification is chosen such that the2-dimensional array only sees the focal volume, without seeing any lightfrom the hollow light cones on the input or exit of the focal volume.The scattered light, accepted by lens 6903B, is reflected by a mirrorand a beamsplitter, through lens 6804, to the detector array. The lenses6803, 6903B, and 6804 are designed to work at infinite conjugates,however lens 6804 could be removed and lens 6803 and lens 6903B could beadjusted to create images of the particles directly onto the detectorarray at finite conjugates. In both Figures, the size of very largeparticles can be measured directly by the size of digitized image toavoid errors in the magnitude of the scattered light from these largeobjects which only scatter at very small scattering angles, where thebackground light is high.

As shown in FIG. 69, the Source 6911B system also uses a concave innersurface whose center of curvature is approximately coincident with thefocal volume. This design produces a focal volume which does not shiftwith change in the refractive index of the dispersing fluid in thesample cell. A concave surface could also be used on the opposing windowto control the focal shift of lens 6903B due to refractive index changeof the dispersant, to maintain sharp focus of the scattered light in theparticle image on the detector array. Again, the center of curvaturewould be coincident with the focal volume. However, FIG. 69 showsanother alternative which may be more flexible and provide better focusprecision. Lens 6903B is attached to a focus mechanism which can movethe lens to various focal positions. This mechanism could be anyappropriate mechanical means, including motor or piezoelectric drivers.The position of lens 6903B, along the optical axis, is changed undercomputer control to maximize particle edge sharpness in the image on thedetector array. This sharpness could be determined by many imagesharpness criteria which include the spatial derivative of the image. Inthe case where the depth of field of lens 6903B is shorter than thedepth of the focal volume of lens 6901B, this focus adjustment can beused to only select particles which are in sharp focus, by measuring theedge sharpness of each particle in the field of view, at three differentfocal positions. Only particles, whose edge sharpness is maximum in themiddle focal position, are sized and counted. In this way, onlyparticles which are accurately sized are counted. The maximum edgesharpness for each particle may vary among different particles which mayhave soft edges. So by measuring the edge sharpness in three differentplanes, the particles which are located in the middle plane can beselected by choosing only the ones whose sharpness is maximum in thatplane. The edge sharpness could be determined by the spatial derivativeof the intensity profile at the edge of each particle. This could alsobe calculated from the maximum of the spatial derivative of the entireparticle, because this usually occurs at the particle's edge. Thederivative could also be calculated from a smoothed version of theimage, if image noise is a problem. This comparison can be done whilethe particles are stationary or by using 3 successive source pulses witha detector array scan during each pulse.

Also, the hollow cone source in FIG. 69 could be replaced by a singlefocused light beam, which is focused through the focal volume andprojected at an angle to the optical axis of lens 6903B, such that it isnot captured by lens 6903B, as shown in FIG. 70. The scatteringinteraction volume is the intersection of the viewing focus of lens7003B and the source focus of lens 7001B. The 2-dimensional detectorarray sees the image of the particles at the focus of lens 7001B, usingonly light scattered from the particles. In this way, the 2-dimensionalarray only sees particles in a very small interaction volume. All of theother focusing mechanisms and options mentioned previously for FIG. 69,also apply for FIG. 70.

Another problem associated with counting techniques is the coincidencecounting error. In some cases, pulses from individual particles willoverlap as shown in FIG. 71, which shows three pulses and the signalwhich represents the sum of those three pulses. In most cases, thesepulses all have the same shape, but with different pulse amplitudes. Forexample, any particle passing through a Gaussian laser beam will producea pulse with a Gaussian shape. The only difference between differentpulses from different particles is the amplitude of the pulse and theposition of the pulse in time. Therefore, the sum of the pulses issimply the convolution of a single pulse with three delta functions,each delta function centered at one of the different pulse positions.The general equation for this sum of pulses is:

S(t)=H(t)ΘΣ(Ai*∂(t−ti))

Where:

Σ=sum over variable it=timeS(t)=the total signal from the overlapping pulses∂(t)=the delta functionti=the time at the center of the ith pulseAi=the amplitude of the ith pulseΘ is the convolution operatorH(t)=the function describing a single particle pulse shape

So the original pulses can be recovered from S(t) by inverting the aboveequation, using H(t) as the impulse response in a Fourier transformdeconvolution or in iterative deconvolution algorithms. As shown by FIG.71, the individual pulse heights and areas cannot be determined from thesum of the pulses S(t). However, through deconvolution the pulses can beseparated as shown in FIG. 72, which shows S(t) and the totaldeconvolved signal resulting after some degree of deconvolution of S(t).Due to signal noise in S(t), S(t) cannot be deconvolved down to separatedelta functions, the deconvolution will usually stop at some pointbefore artifacts are created, leaving separated pulses of finite width.However, these pulse heights will be proportional to the actual heightsof the original separated pulses. So that by using a single scale factoron the deconvolved signal, all of the individual pulse heights willagree with those of the original separated pulses. FIG. 73 shows thisscaled deconvolved result along with the original separated pulses toshow that the separated pulse heights are recovered by the decovolutionprocess. This technique can be applied to any time signals which haveoverlapping pulses of the same shape, such as found in particlecounting. For most laser beams, H(t) will be a Gaussian. However, insome cases, where the laser beam has been apodized or truncated toreduce the large intensity variation, H(t) will take on the functionalform describing the signal vs. time profile of a single particle passingthrough that beam, which may be flat-topped Gaussian, rectangular, etc.

FIGS. 74 through 77 show particle shape measuring systems which combinethe concepts of FIGS. 29 through 31, and FIGS. 42 through 45. FIG. 74shows one system in the first scattering plane of multiple scatteringplanes. A three scattering plane system is shown, but as mentionedbefore, any number of scattering planes may be needed to describe theshape of more complicated particles. The lens 7404 and lens 7405 systemsuse multiple detector elements to measure scatter in each of thescattering planes on one detector array/lens assembly, which ispreferably in the focal plane of each lens. The lens 7407 and lens 7408systems are repeated in each of the scattering planes to measure thehigh angle scattered light. Pinhole 7411C and pinhole 7411 can bereplaced by apertures which are appropriate to the shape of the sourcebeam spot crossection, such as elliptical or rectangular for laserdiodes These detection systems are aligned as shown in FIG. 77, so thateach scattering plane element on multi-element detector A andmulti-element detector B measures in the same scattering plane as thecorresponding lens 7407/lens 7408 aperture openings. For example maskopenings 7421C and 7421D, measure scatter in the same scatter plane asdetector element 7701A; and mask openings 7702C and 2D, measure scatterin the same scatter plane as detector element 7702A. Some possibleconfigurations of the multi-element detectors are shown in FIG. 76. Thisconcept combines the two concepts described earlier in FIGS. 29-31 andFIGS. 42-45. There is one lens 7404/lens 7405 system with both lens 7404and lens 7405 (through beamsplitter 7431) centered on the optical axisof the source to measure low angle scatter. Each detector element, shownin FIG. 76, is aligned to view the same scattering plane as thecorresponding element on the other multi-element detector, but all threescattering planes are measured by the same multi-element detector,through either lens 7404 or lens 7405. The three Lens 7407/lens 7408systems, which measure the higher angle scatter, each have at least oneaperture (instead of 3 elements for each of lens 7404 or lens 7405) foreach lens with shapes like those in FIG. 76 (7701C, 7702C, 7703Capertures have the same (or similar) shape as the detector elements inmulti-element detector A and 7421D, 2D, 3D have shapes similar to thosein multi-element detector B). As before, the ratios of the correspondingdetectors C to D and the ratio of each element on the multi-elementdetector A to the corresponding element on multi-element detector B,provide the particle dimension parameter for the correspondingscattering plane. These parameters are then combined using a lookuptable, search algorithm, or regression algorithm to solve for theparticle shape. As before, to solve for the dimensions of a rectangularparticle with arbitrary orientation, parameters in at least 3 scatteringplanes must be measured. The optimal separation of these planes in theplane of FIG. 77 is approximately 120 degrees, with one of the planesbeing parallel to the flow direction (because many particles will alignwith the flow direction). The search algorithm will take an initialguess at the width, length, and orientation angle, and then calculatethe three parameters for that guess and then compare those parameters tothe measured ones to generate a change in the width, length, andorientation for the next guess and then go through the same loop again.As this loop is repeated, the change in the width, length, andorientation diminishes as the algorithm approaches the true width,length, and orientation of the particle. Optimization algorithms such asNewton's method, global optimization, or Levenburg Marquardt could beused. The three dimension parameters could also be replaced by the fullset of 12 detector signal values (6 for detectors A and B and 6 fordetector sets C and D) for input to these search or optimizationalgorithms. This would be the case for 3 scattering planes. Forparticles with more complicated shapes, measurements in more scatteringplanes would be needed to solve for the shape parameters and thearbitrary orientation, but the same methods would be used to search forthe solution. The corresponding elements in detector C and D and indetector A and B could also be detector segments which view differentranges of scattering angle instead of different angular weightings (asshown in FIG. 76) of the same range of scattering angles. Any of thedetector or mask designs described in this application could be used,including multiple scattering angular ranges on each mask in eachscattering plane or detector/mask designs using radial weightingfunctions Wijs (as described later). For example, mask 7421C could havea different weighting function Wijs than 7421D, so that the ratio ofthese two signals is indicative of size. The use of the use of differentangular weightings may provide larger size range because when theparticles become very large, very little light may fall on the higherangle detectors and the ratio of high to low angle signals will becomemulti-valued. The ratio of 2 detectors with different angular weightings(FIG. 76) will have a smooth monotonic size dependence over a large sizerange.

FIG. 75 shows the use of spherical window shape on the sample cell toavoid focal shift of the focused source spot and of the focal viewingspot of the collection optics as the refractive index of the dispersingfluid is changed. The center of curvature for each surface on eachspherical window is at the beam focal position in the sample cell. Thebottom portion of FIG. 75 shows a spherical cell with an inlet tube,which ends just above the focal spot of the source beam. This cell isplaced into a flow loop as shown in FIG. 13, where the pump pulls thedispersion from the outlet and returns dispersion to the inlet. In thisway, homogeneous dispersion passes through the source beam directly fromthe inlet. Regions far from the inlet, in the spherical cell, may haveinhomogeneous particle dispersion, which may not be representative ofthe entire particle sample. Also when the flow loop is drained, thisorientation of the spherical cell will drain completely without leavingresidual particles to contaminate the next particle sample.

Another concept for measuring the shape and size of small particles isshown in FIG. 78. This system consists of two scatter collectionsubsystems: the first subsystem using lens 7813 and detector array 7821and the second subsystem using a segment of a nonspherical mirror anddetector array 7822. Detector array 7821 measures scattered light at lowscattering angles and detector 7822 measures light scattered at highscattering angles. The light source is spatially filtered by aperture7801 and lens 7811. The spatially filtered beam is then focused, by lens7812, into a spherical sample cell (see FIG. 75) which contains theflowing particle dispersion. FIG. 78 does not show the inlet and outletportions of the cell which are shown in FIG. 75. If the source beamalready has appropriately attenuated components at higher divergenceangles, then Lens 7811 and aperture 7801 can be eliminated and lens 7812can focus the source directly into the sample cell. The sample cellshould have spherical shaped windows (also see FIG. 75) to minimize thefocal shift of the light beam focal spot, due to changes in therefractive index of the dispersant and to reduce Fresnel reflections. Ifthis focal shift or Fresnel reflections are not a problem, planarwindows can be used on the sample cell as shown previously. Thescattered light from the particles is focused through aperture 7802 bylens 7813. Aperture 7802 is in the image plane of the focal spot of thesource inside of the sample cell. As shown previously in FIGS. 43 and45, aperture 7802 will restrict the size of the scattering interactionvolume which can be seen by detector array 7821 so that the probabilityof detecting more than one particle in the scattering interaction volumeis small. The light passing through aperture 7802 is detected by adetector array, as shown in FIG. 79, for example. The unscattered sourcelight beam is either blocked at lens 7813 or passes onto a centraldetector element on detector array 7821 to monitor source beam intensitydrift. The beam may also pass through a hole in the center of detectorarray 7821. The detector array contains 18 separate detector elements(numbered 1 through 18 in FIG. 79). Element 1 measures the approximateoptical flux of the unscattered light. Element 2 measures the low anglescatter for all scattering planes. Elements 3 through 18 measure thescattered light in 8 different scattering planes (2 detection sides perscattering plane for a total of 16 detectors). For example, detectorelement 4 and detector element 12 measure the positive and negativescattering angular ranges for a single scattering plane. Actually, eachscattering plane is the sum of scattering over a small range ofscattering planes, around the center scattering plane for that wedgesegment. Sometimes the positive and negative angular ranges will be thesame, if the intensity is uniform across the particle and if thecrossection of the particle in the scattering plane has rotationalsymmetry about an axis perpendicular to the scattering plane. Then onlydetectors 3 through 10 (half of the detector array) would be needed tocover all of the scattering planes. This source uniformity could beinsured by using an appropriate attenuation profile across the beam ataperture 1 or diffractive beam shaper as discussed previously. If theintensity uniformity of the source focused spot or particlecrossectional symmetry cannot be insured, the positive and negativesides of each scattering plane should be measured separately as shown inFIG. 79. The scattering angle range for detector 1 is limited by thesize of lens 7813. Typically, a single lens can measure up to scatteringangles of approximately 60 degrees. The nonspherical mirror segmentcollects light scattered at higher angles and focuses this light throughaperture 7803, which is also in an image plane of the source focal spotin the sample cell. The shape of the nonspherical mirror is designed tominimize the aberrations between the source focal plane in the samplecell and aperture 7803. For example, the nonspherical mirror could be asegment of an ellipsoid of revolution, where the source focus in thesample cell and aperture 7803 are each located at different foci of theellipsoid. This aperture 7803 defines a restricted scattering volume asshown previously in FIGS. 43 and 45. The light passing through theaperture is projected onto a second detector array, which is similar tothat shown in FIG. 79. However, elements 1 and 2 will not be needed fordetector array 7822 because they are only effective at low scatteringangles, where the scattered intensity does not change significantly forvarious scattering planes. Detector arrays 7821 and 7822 are oriented sothat the bisector of element 3 is parallel to the particle flowdirection. Then each element on detector array 7822 will provide thescattered light signal at higher scattering angles for the samescattering plane of the corresponding detector element in detector array7821. For each scattering plane, the signals from elements 1 and 2, the2 elements (for example elements 4 and 12) in that scattering plane fromdetector array 7821, and the 2 corresponding elements in that scatteringplane from detector array 7822 will determine the “effective dimension”in that plane for that particle. Since these calculated “effectivedimensions” are not totally independent of each other, they must becalculated from a set of simultaneous equations, one equation from eachscattering plane. However, the advantage using many scattering planes isthat the directions of the minimum and maximum dimension can be foundquickly by comparing the ratio of the high and low angle scattering foreach scattering plane. Fewer scattering planes would require much morecomputation time to solve for the dimensions of a randomly orientedparticle, using iterative inversion of the equations. However, when manyscattering planes are measured, the major and minor axes, andorientation, of the randomly oriented particle can be found quickly byinspection of flux ratios (see later in FIGS. 89, 102, and 103). One ofthe scattering planes should be parallel to the flow of the particles,because the major or minor axis of each particle is more likely to beparallel to the flow direction, particularly in accelerating flow whichmay occur from a crossectional area change in the sample cell. Thiscrossectional area change may be designed into the flow path to providethe flow acceleration and particle orientation parallel to one of themeasured scattering planes. The techniques shown in FIGS. 74 and 76could also be used in the FIG. 78 system by replacing the system ofaperture 7802 and detector array 7821 or aperture 7803 and detectorarray 7822 (all from FIG. 78), with pinhole 7411, beamsplitter 7431,lenses 7404 and 7405, and multi-element detectors A and B (all from FIG.74).

In order to increase the range of dimensions which can be measured, morescattering angular ranges must be measured. For example, FIG. 80 shows adetector array which measures two scattering angle ranges for each ofthe positive and negative scattering sides of each scattering plane. Forexample, elements 4 and 20 are low and high angle ranges for thepositive scattering side and elements 12 and 28 are low and high angleranges for the negative scattering side of the same scattering plane.These types of detector arrays are easily fabricated in custom siliconphotodetector arrays. When very small particles are measured, siliconphotodetector arrays may not have sufficient signal to noise to detectthe very small scattering intensities. In this case, photomultipliers oravalanche photodiodes may be used, but at much greater expense formanufacture of custom arrays. One solution to this problem is to replacethe custom detector array with an array of diffractive, Fresnel, orbinary lenses and rout the light from each element of the diffractiveoptic array to a separate element of a commercially available(inexpensive) linear or 2-dimensional detector array, which could bemade of PMT (photomultiplier) elements. However, it is claimed that anydiffractive optic array could be replaced by a detector array withelements of the same shape, if that option is affordable. Arrays ofconventional curved surface lenses, diffractive lenses, Fresnel lenses,or binary lenses are all included in the terms optic array ordiffractive optic array used in this application. The diffractive opticarray would consist of a separate diffractive lens structure coveringthe aperture of each detector element shape in FIG. 79 or 80. Eachdiffractive lens would have a separate optical axis. Therefore, eachdiffractive lens element (or segment) would focus the scattered lightwhich is captured by the aperture shape of that lens element, to aseparate point behind the lens array. FIGS. 81 a and 81 b show a lensarray, where each detection element section contains a lens with adifferent optical axis. This idea will work for any types of lensarrays: spherical, nonspherical, diffractive, binary, and Fresnellenses. FIG. 81 a shows a front view of the diffractive or binary lensarray, where the curved lines inside each detection element segmentrepresent each diffractive optic structure, whose center is the opticalaxis of that lens element. The optical axis, of the elementcorresponding to detector element 1 in FIG. 80, is approximately in thecenter of that element. The optical axis, of the element correspondingto detector element 2 in FIG. 80, is located off of center of the arrayto shift the optical axis away from that of element 1.

To demonstrate this concept, consider the elements with optical axesmarked with “x”, in the front view (FIGS. 81 a and 81 b) and side view(FIG. 82) of FIG. 81, and the corresponding element numbers in FIG. 80.FIG. 82 shows the paths for light rays which pass through aperture 7802in FIG. 78. The aperture in FIG. 82 could be aperture 7802 or aperture7803 in FIG. 78. The lens element for detection element 1 collects thelight from the unscattered light beam and focuses that light into fiberoptic 8201, as shown in FIG. 82. The annular lens element for detectionelement 2 collects the scattered light at the lower scattering anglesand focuses that light into fiber optic 8202, as shown in FIG. 82. Allof the light from the annular segment of element 2 is focused to onefiber optic, because that annular section is an annular section of onelens element with an optical axis which is shifted from the center ofthe lens array. FIG. 82 also shows the scattered light focused by otherlens elements in the same scattering plane into fiber optics 8203, 8204,8205, and 8206. Each lens element has a separate optical axis so thatlight passing through aperture 7802 (FIG. 78) will be focused into aseparate fiber optic for each lens array element, which are shaped tocollect the scattered light over the appropriate range of scatteringangles for each scattering plane. Each lens element focuses the lightfrom that element into a separate fiber optic, which carries that lightto a separate element of a detector array, which may be any type ofdetector array, including 2 dimensional array or linear arrays. Eachfiber optic might also carry light to separate detectors, which are notin an array. Therefore, the detector array does not need to have theshapes of the lens elements so that commercially available (non-custom)detector arrays can be used. And also the detector elements can be muchsmaller than the lens elements, providing much lower noise and lowercost. The cost of fabricating the custom lens array is much less thanthe cost of fabricating a custom photomultiplier detector array orsilicon detector array. Spherical lens arrays can be molded into plasticor glass. And diffractive lens arrays can be molded or patterned(lithography) into nearly planar plastic or glass plates. The choice ofpositions for the optical axis for each element should be optimized toreduce optical aberrations. In some cases, the optical axis may lieoutside of the lens element. Also, the optical axes could be arranged sothat the focused array of spots conforms to the configuration of a 2dimensional detector array so that the spots can be focused directlyonto the detector array, eliminating the fiber optics. This could alsobe done with linear arrays by creating a linear array of optical axes inthe lens array. In each case, fiber optic or detector, the aperture 7802or 7803 in FIG. 78 will be the limiting aperture. Each fiber optic core(or detector element which replaces each fiber optic) is underfilled bythe scattered light image of aperture 7802 or 7803.

The same technique can be used for aperture 7803 by replacing detectorarray 7822 (see FIG. 78) with a lens array whose elements are coupled toa separate detector array through fiber optics (or directly coupled tothe detector array, without fiber optics, as described above). In thiscase, elements 1 and 2 may not be needed, because the scattered lightdistribution from the non-spherical mirror segment has a hole in thecenter where low scattered light is not captured. The high anglescattering should be separated into different scattering planes due tothe high degree of asymmetry in the scattering pattern at higherscattering angles, so the scattered light in annular segments ofelements 1 and 2 would not be as useful. However for large particles,elements 1 and 2 could be broken up into multiple scattering planedetectors to determine particle shape.

This lens array idea is most effective for large numbers of detectionelements. For smaller numbers of elements, each element could have aseparate wedge prism behind it to divert the light to a lens which wouldfocus it onto a particular fiber optic or detector element. But stillthe point is to eliminate the need for a custom detector array, toreduce the detector element size to reduce noise, and to allow use ofhighly sensitive detectors such as photomultipliers, which have limitedcustomization.

Quadrant detectors are commercially available for most detector types,including silicon photodiodes and photomultipliers. FIG. 83 shows amethod to use two quadrant detectors to measure scattered light from 8adjacent scattering planes by using a mask which is positioned on top ofthe quadrant detector. Each scattering plane actually covers a range ofscattering plane angles, as defined by the angle Ø in FIG. 84. The firstquadrant detector replaces each of the detector arrays in FIG. 78. Thesecond quadrant detector captures scattered light at the same distancefrom the aperture 7803 (or aperture 7802) as the first quadrant detectorby diverting a portion of the beam with a beam splitter placed on frontof the first quadrant detector. Each mask is designed and each quadrantdetector is oriented as shown in FIG. 83, so that all 8 scatteringplanes are measured by the two quadrant detectors. In this way, twoinexpensive quadrant detectors can measure the equivalent scatteringplanes measured by one expensive custom 8 element custom detector array.Typically, the central portion of the mask is designed to block theunscattered light from the source beam and to define a minimumscattering angle for each detector element. The detection conceptsdescribed in FIGS. 79, 80, 81, 82, and 83 can also be used in the otherparticle shape measuring optical systems, which were describedpreviously in this disclosure.

FIG. 84 shows a diffractive optic, where different segments consist oflinear diffractive gratings which are designed to diffract nearly all ofthe light into one diffraction order. This diffractive optic is used ina hybrid diffractive/conventional lens system as shown in FIG. 85. Thediffractive optic is normal to the optical axis of the optical system.The aperture in FIG. 85 is the same as aperture 7802 in FIG. 78. Andthis design can also be used with aperture 7803 in FIG. 78, without theneed for the central hole and annular ring segment, because aperture7803 passes only high angle scatter. Consider the case with aperture7802 in FIG. 78. The scattered light is collected by the lens in FIG.85. The diffractive optic (as shown in FIG. 84) in the back focal planeof the lens, diffracts the light incident on each segment of thediffractive optic into various directions. Each direction isperpendicular to the grating lines (see FIG. 84) in each segment. Whenthe aperture hole is small and only single particles are measured, thediffractive optic does not need to be placed in the back focal plane ofthe lens, but the diffractive lens array must be scaled to match themarginal rays (the ray of highest scattering angle) of the lens in theplane in which it resides. The light from each segment is nominallyfocused to the image plane of the aperture. However, the light from eachsegment is focused to a different position on that plane, because thelinear grating structure in each segment is oriented in a differentdirection, or has a different grating period, from the gratingstructures in other segments. Each wedge segment of the diffractiveoptic is split into 2 sections, each with a different grating linespacing and diffraction angle. These 2 wedge shaped segments collectscattered light in 2 different angular ranges in each of variousscattering planes. For example, scattering planes 8401, 8403, and 8405are shown in FIG. 84. In addition, there is a central hole and asurrounding annular region. The central hole passes the unscatteredlight beam and the surrounding annular region collects scattered lightat very low scattering angles in all scattering planes. At lowscattering angles, the scattered light is not strongly dependent uponscattering plane and this annular segment provides a measure of very lowangle scattering (which contains less shape information) to be used aswith the scattering data from each of the scattering planes to determinethe particle dimension in that plane. FIG. 85 shows the light rays inone of the scattering planes. FIGS. 84 and 85 show the case where thespatial frequency of the lower scattering angle segments is higher thanthe spatial frequency of the higher scattering angle segments. Hence theseparated beams cross each other after the diffractive optic, becausethe diffraction angle of the lower scattering angle segments is higherthan that for the higher scattering angle segments. This could also bereversed, where the spatial frequencies are higher for the higherscattering angle segments. In this second case, the focused beams wouldstill be separated at the plane of the fiber optics, but the beams maynot cross each other.

The shape of detector array or optic array elements is not limited towedge shape. Other shapes such as linear shapes shown in FIG. 33 couldbe used. Also each grating structure of a certain spatial frequency andorientation could be replaced by a prism of a certain wedge angle andorientation so as to deflect the light in the same direction as thegrating structure.

This method can also be used to measure “equivalent particle diameter”without any shape determination. In this case, a diffractive optic asshown in FIG. 86 could be used in FIG. 85. This diffractive opticconsists of annual rings which define multiple scattering angle ranges.The signals from these annual rings are independent of particleorientation and will only provide “equivalent particle diameter”. Theorientation (or grating line spacing) of the grating structure in eachannular ring is different from the orientation (or grating line spacing)of any other annular ring to separate the focused scattered light ofeach annular ring into different detectors as shown in FIG. 85.

Any of the masks or detector structures, including those in FIGS. 76,77, 79, 80, 81, 82, 84, 85, 86, and 87, may be replaced by customholographic or binary optic elements which are designed to optimize theshape of the signal vs. particle dimension of each detector element. Forexample, some higher scattering angle signals and ratios of scatteringsignals will show multivalued functionality, where the same value of thefunction occurs at two different particle sizes due to minima in thefunction. Also the function may have a very nonlinear dependence uponparticle dimension, with regions of low sensitivity to dimension value.In these cases, custom holographic or binary optics can be designed withangular transform properties which will reduce these signal distortions.These type of optics can provide a wide range of transformfunctionality, which describes how the direction of an incident ray ateach incident angle is changed by the optical element at each positionon the element. These optics are usually computer generated as surfacestructures, on a substrate, which can be replicated inexpensively bymolding from a computer generated master or by electron beam etching ofthe surface. The characteristics of these structures can be optimized byusing the scattering program to produce the scattering vs. angle in allscattering planes, a propagation program to calculate how this scatteredlight is redirected by the holographic or binary optic element, and analgorithm describing how this transformed light is collected by eachdetector element. An optimization program uses these three programs toproduce the detector signal response as a function of holographic orbinary optic parameters. The optimization program iteratively adjuststhese optic parameters until the optimal form of the detector vs.particle dimension is obtained.

When using a photomultiplier (PMT), one must prevent the detector fromproducing large current levels which will damage the detector. Thisdamage could be avoided by using a feedback loop which reduces the anodevoltage of the PMT when the anode current reaches damaging levels. Inorder to avoid non-linear behavior over the useful range of thedetector, the change of anode voltage should be relatively sharp at thecurrent damage threshold level, with very little change below thatlevel. The response time of the feedback loop should be sufficientlyshort to prevent damage. The feedback signal could also be provided by apremeasuring system as shown in FIGS. 49, 49B, and 51.

Another important point is that any of the scattering techniquesdescribed in this disclosure can be applied to particles which areprepared on a microscope slide (or other particle container), which isscanned through the interaction volume instead of flowing a particledispersion through the interaction volume. This provides someadvantages: the particles are confined to a thin layer reducing thenumber of coincidence counts and the detection system could integratescattered light signal for a longer time from smaller particles, toimprove signal to noise, by stopping the scan stage or reducing the scanspeed when smaller particles are detected (this can also be accomplishedby slowing the flow rate in the dispersion case). However, preparing aslide of the particles for analysis, greatly increases the samplepreparation time and the potential for sample inhomogeneity. When acover slip is placed onto the dispersion, the smaller particles areforced farther from their original positions, distorting the homogeneityof the sample. This method can also be used in dynamic scattering cases(heterodyne detection with flow) by moving the microscope slide with aknown velocity through the source beam.

The scattering signal currents from elements on these detector arraysare digitized to produce scattered signal vs. time for each detectorelement. All detectors could be digitally sampled simultaneously (usinga sample and hold or fast analog to digital converter) or each detectorcould be integrated over the same time period, so that signal ratiosrepresent ratios of signals at the same point in time or over the sameperiod of time and same portion of the source beam intensity profile.The data from each detector element is analyzed to produce a singlevalue from that element per particle. This analysis may involvedetermining the time of maximum peak of the detection element withlargest scatter signal and then using the same time sample for all ofthe other detection elements. Also the peak can be integrated for alldetection elements to produce a single value for each element. Also themethods described previously for pulse analysis can be employed,including the methods (FIG. 28) for eliminating events which are notparticles. The final single value for each detector element representsthe scattered light flux collected by that element. In the followinganalysis, the following definitions will be used:

The integral of F(x) between x=x1 and x=x2 is given by:

INT(F(x),x1,x2)

The sum of terms of Fi(x) over index i from i=n to i=m is given by:

SUM(Fi(x),i=n,i=m)

Where Fi(x) is the ith term

Each scattering angle corresponds to a radius, measured from the centerof the source beam, in the detection plane. For the case shown in FIG.78, z is the distance between aperture 7802 and detector 7821 (orbetween aperture 7803 and detector array 7822). Then the relationshipbetween scattering angle θ and the radius r on the detector is given by:

r=z*tan(Mθ)

where M is the angular magnification of the optical system (angularmagnification of lens 7813 for detector array 7821 and the nonsphericalmirror segment for detector array 7822). In the case of aperture 7803and detector array 7822, the 0 in the above equation is related to theactual scattering angle through a simple equation which describes theangular transformation of the nonspherical mirror segment. This angulartransformation can also be nonlinear for certain types of optics, but inany case there is a one to one correspondence between scattering angleand position r on the detector, mask, or diffractive optic plane. And ris measured from the center of the scattering pattern or the center ofthe source beam on that plane.

Consider the case of rectangular particles, with dimensions da and dband rotational orientation α, as shown in FIG. 105. Then the scatteredflux (flux integrated over the pulse, peak flux value of pulse, etc.)collected by the ith detector element can be described by:

Fij=INT(I(da,db,α,Øi,r)*Wij(r),r1ij,r2ij)

I is the scattered intensity. Øi is the bisecting angle of theintersection of the ith scattering plane with the detector plane in thedetector plane, as illustrated in FIG. 84 for scattering plane 8403. Thescattering plane (which contains the scattered ray and the incidentlight beam) is perpendicular to the detector plane (which is the planeof FIGS. 79, 80, and 83 for example). Wij(r) is the weighting functionof scattered light as a function of r for the jth detector aperture,with limits between r1 ij and r2 ij, of the detector for the ithscattering plane. Notice that Ø and α are corresponding angles; Ø is inthe detector plane and α is in the particle plane (FIG. 105 forexample). If the scattering distribution changes significantly with Ø,within a single scattering plane detector, then the scattered intensitymust be integrated over that detector in both Ø and r:

Fij=INT(I(da,db,α,Øi,Ø,r)*Wij(Ø,r),r1ij,r2ij,Ø1ij,Ø2ij)

where INT is now a 2-dimensional integral over Ø and r.

Fij=INT(I(da,db,α,x,y)*Wij(x,y),x1ij,x2ij,y1ij,y2ij)

-   -   for a conventional detector array (such as a CCD array) with        pixels on a rectangular coordinate system in x and y, where INT        is a 2-dimensional integral in x and y space. In this case the r        and Ø (or Øi) coordinates are replaced by x and y using the        conversion relationships:

x=r cos(Ø) and y=r sin(Ø)

Let F1 be the flux measured on detector element 1 in FIG. 80 and let F2be the flux measured on detector element 2 in FIG. 80. Then thefollowing sets of simultaneous equations can be formed to solve for thedimensions da, db, and random orientation, α, of the particle, where Riis a ratio of two fluxes.

Fi = Fij equation set: [Fij]m = [Fij]t Ri = Fij/Fik equation set:[Fij/Fik]m = [Fij/Fik]t Rijk = Fik/Fij equation set: [Fik/Fij]m =[Fik/Fij]t Ri = Fij/F2 equation set: [Fij/F2]m = [Fij/F2]t Ri = Fij/F1equation set: [Fij/F1]m = [Fij/F1]t Ri = Fij/Fkj equation set:[Fij/Fkj]m = [Fij/Fkj]t Ri = Fij/Fkn equation set: [Fij/Fkn]m =[Fij/Fkn]t Ri = FijA/FijB equation set: [FijA/FijB]m = [FijA/FijB]t Ri =FijA/FknB equation set: [FijA/FknB]m = [FijA/FknB]t[X]m is the measured value of X (derived from signals measured by theoptical system detectors) and [X]t is the theoretical function whichdescribes X as a function of the particle characteristics. Some of theseparticle characteristics are unknowns (da, db, and a for example) to besolved from the equation set. Recognize that i indicates the ithscattering plane and ij indicates the jth detector in the ith scatteringplane. FijA and FijB are the corresponding detector elements from twodifferent detector arrays (A and B), each with a different Wij (r), asshown in detector pairs A and B in FIG. 74, and diffractive optics 8701and 8702 in FIG. 87. This equation also holds for more than twodetectors (Ri=FijC/FijB, etc.). Also, for all other Ri equations, Wijcan be the same or different for the numerator F and the denominator Fin the ratio. The above simultaneous equations can be formed from theFij values measured from each particle. Any groups of the aboveequations, for any values of i, j, k, n, A, and B, can be solved for da,db, and a (or other particle characteristics) by using various search,optimization, and regression methods. In most cases, the equations willbe non-linear functions of these unknowns, requiring iterative methodsfor solution. The computation of theoretical values for scatteredintensity I(da, db, α, Øi, r), of nonspherical particles, requires longcomputer time. This is particularly problematic as this computation mustbe accomplished for each counted particle. Also numerical integration ofthese functions to produce Fij values during the iterative optimizationprocess requires far too much computer time. This computer time can bereduced by fitting a series of explicitly integratible functions to eachof the theoretical I(da, db, α, Øi, r) functions. For example considerthe following power series form for the I(da, db, α, Øi, r) and Wij(r)functions:

Wij=SUM(Qp(j)*(r̂p),p=0,p=pmax)

Ii=SUM(Cm(da,db,α,Øi)*(r̂m),m=0,m=mmax)

Where x̂p=x to the pth power and x*y=product of x and y.

Fij=INT(I(da,db,α,Øi,r)*Wij(r),r1ij,r2ij)

Fij=INT(SUM(Cm(da,db,α,Øi)*(r̂m),m=0,m=mmax)*SUM(Qp(j)*(r̂p),p=0,p=pmax),r1ij,r2ij)

Fij=SUM(Bq(da,db,α,Øi)*(r2iĵ(q+1))/(q+1)),q=0,q=pmax+mmax)−SUM(Bq(da,db,α,Øi)*(r1iĵ(q+1))/(q+1)),q=0,q=pmax+mmax)

Then the previously listed sets of simultaneous equations can be formedfrom these equations for Fij. Where Bq are coefficients which areproducts of values of Cm and Qp, which are all known functions of da,db, α, and Øi. This concept can easily be extended to other particletypes (just assume da and db to be the major and minor axes for anelliptical particle) and particles with more dimensions, such aspentagons, etc. In each case, the model must expand to account for theadded dimensions dc, dd, de, etc.

Fij=INT(I(da, db, dc, dd, de, . . . , Øi, r)*Wij(r),r1ij,r2ij)

In order to solve for particle types with larger number of dimensions(i.e. octagons, etc.), sufficient scattering planes and detectors mustbe used to provide a fully determined set of simultaneous equations. Inother words, the number of equations should be greater than or equal tothe number of unknowns, which include the dimensions, da,db,dc, . . .etc. and the particle orientation, α. However, as indicated before, thesolution of these equations can be computationally time consuming. Themeasurement of scattered light in many scattering planes can reduce thecomputational time, because the extrema of the dimension function can befound quickly. For example, take the case of the rectangular particle,where da, db, and a could be solved for with only measurements in 3scattering planes. The solution of these 3 equations may requireiterative search and much computer time per particle. However, ifscattering is measured in many more scattering planes, the major andminor axes of the rectangle can be determined immediately, eliminatingthe requirement for determining the particle orientation a or reducingthe range of a for the search solution. For example, if we interpolate aplot of Ri vs. Øi (or Rijk vs. i), we will obtain a function (orfunctions) with a maximum at Ømax and a minimum at Ømin, as shown inFIGS. 89, 102, and 103. If Ri is the ratio of the high angle fluxdivided by the low angle flux in the ith scattering plane, then thedirection Ømin will provide major axis and the direction Ømax willprovide minor axis of the particle; and the R values for thosedirections will provide the particle dimensions in those directions. Anexample of the rectangular case is shown in FIG. 102 for a rectanglewith 1:5 aspect ratio. The scattered flux in the higher scattering angledetector element (Fi2) is divided by that of a lower scattering angleelement (Fi1) to produce a ratio Ri12 for each scattering plane angleØi. Øi equals 90 degrees at the maximum of Fi2 and Ri12, indicating thedirection parallel to the smallest dimension of the rectangle. In thisway the orientation and shorter dimension of the rectangle can bedetermined immediately from the direction Øimax=90 and values of Fi1,Fi2, Ri12 for that scattering plane. And the longer dimension isdetermined from the values of Fi1, Fi2, Ri12 for the scattering planewhich is perpendicular to the plane at 90 degrees, Øi=0 degrees,assuming a rectangle. For example the equation for I(a,b) could be usedto calculate the flux values Fi1 and Fi2 for the major and minor axisscattering planes, as a function of dimensions A and B of the rectangle.Then these functions are inverted to provide dimensions as a function ofFi1, Fi2, and Ri12 for the major and minor axis scattering planes. Thiscould also be accomplished with a search routine. This process is simplein this case because in the directions of the major and minor axes Fijare approximately only a function of the dimension in that plane. Hencethe two dimensions can be determined independently. This technique canbe extended to particles with more dimensions, as shown in FIG. 90,where multiple extrema indicate the 0 direction and effective particledimension in that direction. The case for a triangle shaped particle isshown in FIG. 103, where a maximum in Fi2 and Ri12 is shown in eachscattering plane which is perpendicular to each side of the triangle.The peak locations provide the particle orientation and fastdetermination of dimensions using the simultaneous equation sets above.For the case where the particle shape is not assumed, the relative Øiorientation of the peaks in the Fi2 or Ri12 function indicate the shapeand orientation of the particle, and the values of Fi2 or Ri12 indicatethe dimensions. In some cases these dimensions may not be completelyindependent, requiring iterative minimization of the RMS error betweenFij (measured) and Fij (theoretical) using various search, optimization,and regression methods (such as Newton's method, Levenburg-Marquardtmethod, etc.). These methods use a first quess to the unknowns (all thedimensions and a) from which the Fij (theoretical) is calculated. Thenthe difference between Fij (measured) and Fij (theoretical) is used torefine the next guess for the unknowns from which the next Fij(theoretical) is calculated. The change to the particle parameters(unknowns) to calculate the next Fij (theoretical) or Rijk(theoretical)is determined by the type of optimization algorithm (Newton's method,Marquardt Levenburg, etc.). This iteration loop is repeated until thefit between all Fij(measured)'s and Fij(theoretical)'s is sufficient,where i=scattering plane index and j=detection array element or lensarray element index in a certain scattering plane. This iterative loopis run many times until one (or the sum of both) of the following RMSerrors are minimized.

Error=SUM((Fij(measured)−Fij(theoretical))̂2) summed over all ij

Error=SUM((Rijk(measured)−Rijk(theoretical))̂2) summed over all ijk

Many applications will require only particle characteristics whichcorrelate to some quality of the manufactured product. Examples of thesecharacteristics include: 1) equivalent spherical diameter and aspectratio, 2) maximum and minimum equivalent dimensions as determined fromthe scattering planes with minimum and maximum Rijk, respectively, 3)dimension in the minimum Rijk scattering plane and the dimension in theplane perpendicular to that plane, 4) dimension in the maximum Rijkscattering plane and the dimension in the plane perpendicular to thatplane. The equivalent dimension is the dimension calculated for thatplane as though the plane were a major or minor axis plane using thescattering theory for a rectangle. All of the detector, mask, anddiffractive optic configurations shown in this disclosure are onlyexamples. This disclosure claims the measurement of any number ofscattering angular ranges in each of any number of scattering planes, asrequired to determine the shape and size of each particle.

All segmented detector arrays or lens arrays could be replaced by2-dimensional detector arrays. In this case the inverse 2-dimensionalFourier Transform of the spatial distribution of detector element fluxvalues would produce a direct 2-dimensional function of the particleshape, in the Fraunhofer approximation. The dimensions of the contourplot (perhaps by choosing the 50% contour of the peak contour) of this2-dimensional inverse Fourier Transform function will provide theoutline of the particle directly, for particles which are modeled by theFraunhofer approximation. However, the size range of this type of array(per number of detector elements) is not as efficient as the wedgeshaped scattering plane arrays described previously, because thedetector elements in the commercially available 2-dimensional arrays areall the same size. When the particles become large enough to producescattered light in only the lowest scattering angle detector element,the size determination becomes difficult, because two reliablescattering values are not available to determine the size in thatscatter plane and absolute scatter signals must be used without signalratios. This problem could be solved by using a custom array, where lowscattering angle elements are smaller than larger scattering angleelements. This progression of element size with increasing scatteringangle can also be accomplished with a equal pixel 2-D array whichfollows a lens, holographic optic, binary optic, or diffractive opticwith non-linear distortion. The lens or diffractive optic distorts thescattering pattern so that the pattern is spread out near the center andcompressed more at higher radii (larger scattering angles) in thepattern. In this way, detector elements closer to the center of thepattern will subtend a smaller scattering angular width than elementsfarther from the center. This would increase the size range of thedetector array and still allow use of standard CCD type linear arrays.However, due to the limited dynamic range of most CCD arrays, a singlePMT or other large dynamic range pre-sensor, placed upstream of the CCDarray, could provide some indication of scattering signal level beforethe particle arrives in the view of the CCD array, similar to thesystems shown in FIGS. 49, 49B, 50, 51, 67, and 68. Then the sourcepower level or CCD electronic gain could be adjusted during the CCD datacollection to optimize the signal to noise and fully utilize the rangeof the analog to digital converter on the CCD. Any optical system inthis application can be used as a pre-sensor for any other opticalsystem (the primary system) in this application, by placing thatpre-sensor system upstream of the primary system to quickly measure thescattering properties and adjust the source power level or detectionelectronic gain of the primary system to optimize the detection systemperformance of the primary system, using the same concepts as describedfor FIGS. 49, 49B, 50, 51, 67, and 68.

This wider size range can also be obtained by using different weightingfunctions (Wij) for two different detector elements which view the samerange of scattering angle (or different ranges of scattering angle) inthe same scattering plane, as described previously. As long as the Wijfunctions are different for the two measurements, the ratio of thosescattered flux values will be size dependent over a large range ofparticle size and will be relatively insensitive to position of theparticle in the beam. The Wij function can be implemented in thedetector element shape, as shown in FIG. 76, and/or by placing anattenuation mask, which has varying attenuation along the direction ofchanging scattering angle, over the detector elements of one the arraysor with different Wij functions on each of two or more arrays which seethe same scattering angle ranges and scattering planes. This idea can beimplemented in the system shown in FIG. 78, using the detection moduleshown in FIG. 87. The aperture in FIG. 87 could be either aperture 7802or aperture 7803 in FIG. 78. In this case, the scattered light (andincident beam when used with aperture 7802) is focused by a lens,through a beamsplitter, onto two optical arrays, which are diffractivearrays using conventional lens/diffractive array hybrid as in FIG. 85(or conventional molded or diffractive optics if no single conventionallens is used). The lens arrays (examples are shown in FIGS. 79, 80, 84,86) are used to divert the scattered light from different array elementsto different positions in the image plane of the beam focus in the cellso that the flux from each element can be collected separately by fiberoptics or detectors. The lens array in FIG. 87 is similar to that inFIG. 79, just for illustration, but any of the previous lens arrayscould be used in this design. There is a mask on front of each lensarray which provides selection of center hole (element 1 in FIG. 78) orthe annular ring (element 2 in FIG. 78). This mask also provides lightattenuation which varies along the radius (or scattering angle) of themask, as shown by the transmission function, for example only, in FIG.88. This transmission function can take many forms, but as long as theradial transmission function of mask 8750 is different from the radialtransmission function of mask 8751, the ratio of flux from correspondinglens elements in diffractive optic 8701 and diffractive optic 8702 (ascaptured by the fiber optics or detector elements) will providedimensional information for the particle in the scattering plane of thatelement. For example transmission functions for mask 8750, T1 ij, andfor mask 8751, T2 ij, could have many cases including:

Case 1: T1ij=1(constant transmission), T2ij=r

Case 2: T1ij=r, T2ij=r̂2

where r is the radius in the scattering plane from the center of thelens array. Each value of r corresponds to a different scattering angle.

Then the effective weighting functions are the product of thetransmission functions and the weighting function, Wijs, of the segmentor element shape in the detector array or optic array. For wedge shapedsegments the shape weighting function is:

Wijs=r

Hence the effective weighting functions are:

W1ij=W1ijs.*T1ij

W2ij=W2ijs.*T2ij

R12ij=F1ij/F2ij

Where F1 ij=flux from the jth detector aperture in the ith scatteringplane of detector array 1 or optic array 1Where F2 ij=flux from the jth detector aperture in the ith scatteringplane of detector array 2 or optic array 2

In some cases, wedge shaped detector elements are easily implementedbecause they include the same group of scattering planes throughout therange of scattering angle. When the same wedged shaped elements are usedin both arrays, the transmission functions could provide the differencein Wij. For example one combination could consist of these functions:

T1ij = r{circumflex over ( )}0.5 W1ijs = r W1ij = r{circumflex over( )}1.5 T2ij = r{circumflex over ( )}−2.5 W2ijs = r W2ij = r{circumflexover ( )}−1.5

Many combinations of transmission functions will work. This inventiondisclosure claims the use of any two different W1 ij and W2 ij functions(using transmission and/or shape weighting functions) and using fluxfrom corresponding array elements, one with W1 ij and the other with W2ij. Diffractive optic array 8701 and diffractive optic array 8702 areidentical and they are rotated so that each array segment collectsscattered light from the same scattering plane as the correspondingelement in the other diffractive optic. Then ratio (R12 ij) of lightflux values from these two elements is used to determine the “effectivedimension” of the particle in that scattering plane. However, asdescribed previous, these dimensions are not independent and the fullset of simultaneous R12 ij equations must be used to solve for theactual dimensions.

The radial weighting function Wij can also be used with a singleposition sensitive detector, which uses multiple electrodes to determinethe position of the centroid of the pattern on the detector. As theparticle size decreases, the centroid, as measured through the Wij mask,will move towards larger radial value r, indicating the particle size.

In general, we have two cases for measuring 2 dimensional scatteringdistributions. The detector array can be a set of radial extensions invarious scattering planes (as in FIG. 84) or a 2-dimensional array. Infirst case, we define the array as a function of radius, r, and angle Øin the detector array or optic array plane, as shown in FIG. 84. In thesecond case the array is a standard 2-dimensional array (i.e. CCD array)with elements arranged in columns and rows which are defined as afunction of x and y. The choice between these cases will be determinedfrom the available computer speed, shape constraints, and particle sizerange. In order to measure particle shape statistics of a particlesample, an enormous number of particles must be characterized. Forexample, consider the following case. We are to count particles andcharacterize them into 25 different dimensional classes. Each classcould vary by size or shape. If we want to measure the content of eachclass to within 5% we need to measure 400 particles per class, if thecounting process is Poisson. Therefore we need to measure andcharacterize 10000 particles. If we want the entire analysis process totake 5 minutes, then we have 30 milliseconds per particle to measure anddigitize the scattered light, and solve equations for the shape anddimensions. We could do a full global search for the particleorientation and dimensions using the equations given above. All of theparameters of those equations can be solved from the 2-dimensionalscattered intensity distribution in the plane of the detector array oroptic array. The theoretical 2-dimensional scattered intensitydistribution is calculated using known methods, such as T-matrix andDiscrete Dipole Approximation, (see “Light Scattering by NonsphericalParticles”, M. Mishchenko, et al.). Then this theoretical intensitydistribution is integrated over the areas of each element of detectorarray or optic array. These values for Fij are calculated for variousparticle orientations, α, and various particle dimensions. A globalsearch routine would search among these theoretical Fij sets to find theone which best fits to the measured set of Fij. Then the dimensions ofthat set would be accepted for that particle. While this process mighttake far longer than 30 milliseconds per particle, it would produce themost accurate determination of particle dimensions and shape. This fullsearch method is claimed by this invention because in some cases, userswill be willing to collect data on the optical system computer and thentransfer the raw data off-line to a set of parallel processors whichcontinuously crunch data sets 24 hours per day. And also futurecomputers will be capable of doing these computations in the requiredtime. However, for the users, who want their results in real-time (i.e.within 5 minutes) with present personal computers, some of theshortcuts, as described previously, must be employed. In the case ofprocess control, users need results quickly in order to adjust theprocess parameters in nearly real-time. And also, many times thedetermined shape and size does not need to be precise because theseresults only need to correlate to the quality of their product. Ingeneral a particle with multiple flat edges will produce a scatteringpattern with a radial projection for each edge into a scattering planewhich is perpendicular to that edge. So when the ratio data, Rijk, isplotted vs. Øi (or vs. scattering plane) as shown in FIGS. 90 and 103,one will obtain a maximum in Rijk for each side of a multi-sidedparticle. So evaluation of Rijk vs. Øi will very quickly determine theorientation of the particle's sides and the values of Rijk are then usedin a more limited global search routine, which does not have to searchover all possible orientations of the particle and over all possiblenumber of particle sides. This will dramatically reduce the search time.Also, the “dimension” of the particle in the direction perpendicular toeach side can be determined approximately from Rijk values in thescattering plane which is perpendicular to that side. These values couldbe used directly to determine “approximate dimensions” of the multisidedparticle, without a search algorithm, because the approximate dimensioncan be calculated directly from a theoretical function of Rijk. As theparticle model becomes simpler (i.e. rectangle) the orientation anddimensions are calculated immediately by finding the Ømax and Ømin inthe Rijk vs. Øi, and then using the Rijk values in those two scatteringplanes to calculate the dimensions in those scattering planes. If only afew scattering planes are measured, the Rijk function could beinterpolated or fit to a theoretical function for the rectangle case, tocalculate a more exact orientation, which may be between two adjacentscattering planes.

In general, the values Fij values as a function of size may bemulti-valued in some size regions. Consider the simple case of 3 fluxmeasurements, in each of 3 different scattering angle ranges. The firstcase, shown in FIG. 94, shows integrated flux for wedge shaped elementsover narrow scattering angular ranges 4-6, 28-30, and 68-70 degrees.Notice that the higher angle flux has many oscillations vs. size and ismulti-valued (i.e. for the 68-70 degree flux measurement one absolutelevel can indicate multiple sizes). However, particles at each diameterare uniquely determined by the 3 flux measurements. These oscillationsand multi-valued behavior can be reduced by increasing the width of theangular ranges as shown in FIG. 95 for scattering angular ranges of 1-5,6-30, and 32-70 degrees. However, the width of angular ranges may belimited in heterodyne systems due to loss of interferometric visibilityas shown by FIG. 91.

These concepts can be combined with imaging systems to record the imageof selected particles after they have passed through the interactionvolume. An imaging system could be placed downstream of the interactionvolume, with a pulsed light source which is triggered to fire at thecorrect delay, relative to the scatter pulse time, so that the particlehas flowed into the center of the imaging beam during image capture. Thepulsed light source has a very short pulse period so that the movingparticle has very little motion during the illumination and imagecapture on a CCD array. The particle is imaged onto the CCD array athigh magnification with a lens (microscope objective would be a goodchoice). In this way, particles which meet certain criteria, can beimaged to determine their morphology.

The alignment of aperture 7802 and aperture 7803 in FIG. 78, and otherrelated figures, could be accomplished by running a medium concentrationsample of sub-micron particles through the sample cell. Theconcentration is chosen so that a large number of particles are in theinteraction volume at the same time so that a constant large scattersignal is seen on the detectors. Then the x, y, and z position of eachaperture is adjusted to maximize the scatter signal on the detectors.This adjustment could include the methods described for FIGS. 5 and 6.

Most of the concepts in this application can accommodate aerosolparticle samples, by removing the sample cell and by flowing the aerosolthrough the interaction volume of the incident beam. The effectivescattering angles may change due to the change in refractive index ofthe dispersant.

Many methods in this application have used the heterodyne detection ofscattered light to detect a particle. This is particularly useful forsilicon detectors, which have lower sensitivity than PMTs. The beatfrequency, Fb, depends upon the angle, θm, between the direction ofmotion and the direction of the incident light beam, and upon thescattering angle, θs.

Fb=v(cos(θm)−cos(θs−θm))/w1

Where v is the particle velocity and w1 is the light wavelength in thedispersant. FIG. 91 shows the contours of this function (normalized) vs.θs and θm. Notice that the beat frequency has very strong dependenceupon these two angles. Consider the case where θm is 1 degree and theparticle flow is nearly parallel to the incident beam. Then we obtainthe dependence shown in FIG. 92. If all of the scattered light, over thescattering angular range of interest, from this moving particle werecollected onto one detector in heterodyne mode, the scattered signalwould contain a broad range of beat frequencies and the signal amplitudeat each frequency would indicate the scattering amplitude at thecorresponding scattering angle. Hence, the Fourier Transform of thesignal vs. time from a single heterodyne detector could provide theentire angular scattering distribution from that particle, by using theFourier Transform and the scattering angle to frequency correspondencecurve, as shown in FIG. 92. Using the above equation, scattering angleto frequency correspondence curves could be computed for other values ofθm that might be used.

In some cases, the dynamic range of detectors will not be sufficient tocover the entire range of scatter signals from the particles. Inparticular, particles in the Rayleigh scattering range will producescatter signals proportional to the 6^(th) power of the particlediameter. Photomultipliers can also be damaged by large levels of light.FIG. 93 shows an optical system which uses upstream scatter measurementto control the laser power or detection gain (or anode voltage) for asystem down stream in particle flow to protect photomultipliers, tomaximize the signal to noise, or to avoid detector saturation. Two lightsources, light source 9311 and light source 9312, are combined bybeamsplitter 9321 and focused into the center of the sample cell to twodifferent locations along the particle flow path. Light source 9312could be magnified to produce a larger spot size in the sample cell fordetecting larger particles than the spot from light source 9311.However, the other purpose of light source 9312 is to detect an oncomingparticle before it reaches the focused spot from light source 9311. Thespot from light source 9312 is upstream from the light source 9311 spot.The light from both sources and the light scattered from both sourcespass through lens 9303, which images both light spots to the planes ofthree apertures, 9341, 9342 and 9313. Apertures 9342 and 9313, whichreceive light reflected from beamsplitter 9322, block light from theinteraction volume of light source 9311 but pass light from theinteraction volume of light source 9312. Likewise, aperture 9341, whichreceives light transmitted by beamsplitter 9321, blocks light from theinteraction volume of light source 9312 but passes light from theinteraction volume of light source 9311. Therefore multi-elementdetector 9331 sees only light scattered from light source 9311; andmulti-element detector 9332 and detector 9333 see only light scatteredfrom light source 9312. These multi-element detectors can also bereplaced by the optic array systems described previously. Multi-elementdetector 9332 is operated at much lower sensitivity than Multi-elementdetector 9331, which is operated at maximum sensitivity to detect thesmallest particles. Whenever a particle, which would saturate and/ordamage Multi-element detector 9331, passes through light source 9312spot, detector(s) from Multi-element detector 9332 or detector 9333 willmeasure the larger amount of scattered light and trigger a circuit tolower the power level of light source 9311 or lower the gain (or anodevoltage) of Multi-element detector 9331 so that Multi-element detector9331 will not be saturated and/or damaged when that same particle passesthrough the interaction volume for light source 9311. This pre-sensorsignal can also be used to optimize the signal to noise or dynamic rangeof the downstream sensors, as described previously for FIGS. 49, 49B,50, 51, 67, and 68. The level of adjustment can be variable dependingupon the light level measured by Multi-element detector 9332 or detector9333. Light source 9311 is normally run at maximum power to detect thesmallest particles. Light source 9311 power is only reduced after acalculated delay time after Multi-element detector 9332 detects apotentially damaging or saturating particle scatter signal. After thatparticle passes through the light source 9311 spot, the source 9311power (or gains, anode voltages etc) is reset to maximum. The time delayis calculated from the spacing between the two source spots in thesample cell and the particle flow velocity. The multi-element detectorarrays are in the focal plane of lens 9304 or lens 9305. Notice that thedark solid light rays indicate that multi-element detector arrays 9331and 9332 are effectively, at infinity, in the back focal planes oflenses 9304 and 9305. These lenses place the detectors at infinity sothat the effects of finite pinhole size in apertures 9341 and 9342 donot cause smearing in the scatter pattern. Typically the pinhole sizesare small enough so that lens 9304 and lens 9305 are not needed. Theadvantage of using lens 9302 for both sources is not only the cost ofmanufacture. This design allows the two source spots in the sample cellto be very close to each other, insuring that all particles which flowthrough the light source 9311 spot will have also previously flowedthrough the light source 9312 spot and been detected by multi-elementdetector 9332, even in the event of any flow anomalies (such asnon-laminar flow) in the cell. To provide a large size dynamic range,the sample cell spot size for light source 9312 may be much larger thanthe spot size for light source 9311, in order to measure much largerparticles. Then many particles which pass through source 9311 spot willflow around source 9312 spot. In this case, a third system is addedusing beamsplitter 9323 and aperture 9313. The pinhole of aperture 9313is smaller than aperture 9342 to only pass scatter from the portion ofSource 9312 spot which is directly above the Source 9311 spot. In thisway, detector 9333 will only see the particles which will eventuallypass through the source 9311 spot. So detector 9333 is used to set thesource 9311 power level or detector 9331 gain (or anode voltage) usingthe time delay described above. Multi-element detector 9332 measures thesize of larger particles from a much larger interaction volume asdefined by aperture 9342. For example, the spot sizes in the sample cellcould be 20 microns for light source 9311 and 500 microns for lightsource 9312, but aperture 9313 would only allow detector 9333 to seescatter from a 30 micron portion, of the Source 9312 spot, which isdirectly above the 20 micron spot of Source 9311. The 30 micron portioncould be slightly larger than the 20 micron spot to accommodate slightflow direction misalignment, because the larger size will only triggerthe source 9311 power drop more times than needed, but it will guaranteethat no particle scatter will saturate and/or damage multi-elementdetector 9331.

FIG. 96 shows a variation of the optical system shown in FIG. 78, whichprovides heterodyne detection and measures scattered light over multiplescattering angle ranges and in multiple scattering planes. Heterodynedetection, with the source noise correction methods describe earlier,may provide better detection of small particles. Some light is split offfrom the source light by beamsplitter 9611 and focused into a fiberoptic. This fiber optic passes through an optional optical phase orfrequency shifter to provide an optical frequency shifted localoscillator for the detection of scattered light. This shifter could bean acousto-optic device or moving diffraction grating. The frequencyshift can also be provided by a scanned optical phase shifter (movingmirror or piezoelectric fiber stretcher) whose optical phase is rampedby a sawtooth function to produce an effective optical frequency shiftduring each period of phase ramp. Fiber optic coupler 9621 splits off aportion of the light after the phase shifter and passes this light todetector 9630 which monitors the fluctuations in the light intensity (I2in the previous description of source noise correction) which may be dueto laser noise or amplitude modulation from the optical frequency orphase shifter. Then the source light is finally split into two fibers byfiber optic coupler 9622 to provide local oscillators for both detectionsystems. The light exiting the one fiber from fiber optic coupler 9622is expanded by negative lens 9607 and then focused by lens 9606 throughaperture 9642 (via beamsplitter 9612) to be mixed with the scatteredlight on detector array 9651 (or optic array 9651). Likewise light, fromthe other output fiber of fiber optic coupler 9622, is expanded bynegative lens 9605 and then focused by lens 9604 through aperture 9643(via beamsplitter 9613) to be mixed with the scattered light on detectorarray 9652 (or optic array 9652). In this way, heterodyne detection isaccomplished with laser noise reduction using the equation and methoddescribed previously:

Idiff−I1nb−(R/K)*I2nb=Sqrt(R*(1−R)*S)*Ioc*COS(F*t+A)

Idiff only contains the heterodyne signal. The common mode noise in thelocal oscillator and the heterodyne signal is removed by thisdifferential measurement (see the previous description of the method).Heterodyne detection provides very high signal to noise, if the lasernoise is removed by this equation and method. However, if the heterodynefrequency is only due to Doppler shift of the scattered light fromparticle motion, then the frequency of the heterodyne beat frequencywill depend upon scattering angle and scattering plane (for example, thescattering plane, which is perpendicular to the particle flow, will showzero Doppler frequency shift of the scattered light). The addition ofthe optical phase or frequency shifter provides a much higher heterodynefrequency which is nearly equal for all scattering angles and scatteringplanes, allowing heterodyne detection of particle size and shape. Theonly problem presented by the frequency shifter is that all light thathits the detector, by scatter or reflection, will be frequency shifted.Without the frequency shifter, only scatter from moving particles willcontribute to the heterodyne signal at the beat frequency, so backgroundlight can be distinguished from particle scatter based upon signalfrequency. So when the frequency shifter is used, a background scatterheterodyne signal should be recorded without particles and thisbackground signal should be subtracted from the scatter heterodynesignal with particles present. Addition of an optical frequency shifteralso provides a higher beat frequency and phase sensitive detectioncapability. The signals due to the particle motion and the Dopplereffect have random phase for each particle. So the other advantage ofthe frequency shifter is that the heterodyne signal will have a knownphase (same as the frequency shifter), which could allow for phasesensitive detection (lock in amplifier). As shown before, the signalsfrom this system will consist of a sinusoidal signal with an envelopefunction from a particle's passage through the intensity profile of thesource beam. So all of the techniques described previously forprocessing these signals can be applied to this case.

For the heterodyne systems, as shown in FIG. 96, FIG. 91 shows thefactor between the actual distance moved by the particle along themotion direction and the effective distance representing the opticalphase shift at the detector. Hence this factor is the ratio between theDoppler frequency as computed from the particle motion along thedirection of that motion and the Doppler frequency measured on adetector which measures scattered light from that moving particle at acertain scattering angle. This factor is also the ratio between theoptical phase shift as computed from the particle motion along thedirection of that motion and the optical phase shift as measured on adetector which measures scattered light from that moving particle at acertain scattering angle. In most cases, in order to maintain highinterferometric visibility in the heterodyne signal, the angular rangeof any single detector element (or optic array element) should belimited so that the phase change across the element during the particlespassage is less than approximately 2 pi. For example, if the particlepasses through a distance of 10 light wavelengths during passage throughthe beam, then the factor shown in FIG. 91 cannot change by more than1/10 across the detector element. The dependence in the regions withgreatest phase shift (motion to beam angles of 1 degree or 90 degrees)is plotted in FIG. 99. For this case, most detector elements should belimited to cover less than 5 degrees scattering angle range and the beatfrequencies will change on different elements, which may require aseparate band pass filter for each element. Also the beat frequency willbe different for each scattering plane. One method to eliminate thisdependence is to design the system to have minimal particle motioninduced phase shift by choosing angles, between the particle motiondirection and the beam, of approximately 30 to 40 degrees as shown inFIG. 98, and using the optical frequency or phase shifter (FIG. 96) toprovide the phase modulation at a high frequency, instead of the phaseshift due to particle motion. Then all detector heterodyne signals willhave almost the same frequency and phase, with the high signal to noiseprovided by heterodyne detection. Also the phase modulation signal couldbe used with phase sensitive detection (lock in amplifier) to detect theheterodyne signal. However, two disadvantages of this system are lightreflections and amplitude modulation due to the phase modulator. Withoutthe phase modulator, only scattered light from moving particles willcreate a heterodyne beat signal. However, with the phase modulator andangles between the particle motion direction and the beam, ofapproximately 30 to 40 degrees, all light reaching the detector fromscattering or reflections will be at the beat frequency and will bepassed by the band pass filter. Also the phase or frequency modulatorwill produce some small amount of amplitude modulation in the beam,which may completely overwhelm the particle scattering signal, evenafter it is removed using detector 9630 (FIG. 96) and the differentialdetection described previously. The severity of these problems will bedetermined by the characteristics of the phase or frequency modulatorand the level of light reflections in the optical system.

The system in FIG. 96 could also be designed without fiber optics. Eachfiber optic coupler would be replaced by a beamsplitter and the lightbeams could be routed to lens 9605 and lens 9607 using mirrors andlenses to create a beam focus at aperture 9642 and aperture 9643 throughbeamsplitter 9612 and beamsplitter 9613, respectively. The negativelenses 9605 and 9607 may be needed to expand the beam to fill theangular range of light on each detector array or optic array.

FIG. 97 shows another variation of the optical system shown in FIG. 78.The source beam is split into two beams which cross each other in theinteraction volume in the sample cell. The two beams will create afringe pattern at their intersection, which will modulate the scatteredintensity as a particle passes through the intersection, as shownpreviously in FIG. 18. Lens 9701 focuses the source light into thecenter of the sample cell. However, the light beam is split into twobeams by beamsplitter 9711. These two beams are reflected by mirror 9721and mirror 9722 to cross in the center of the sample cell. One of thebeams may pass through an optical frequency shifter to provide a beatsignal of known phase and/or higher frequency. The advantage of thismethod is that only particles passing through the fringe pattern at theintersection of these dual beams will produce signals at the beatfrequency. This intersection, and aperture 9732 or aperture 9733, definea small interaction volume which reduces coincidence particle counts.Addition of an optical frequency shifter provides a higher beatfrequency and phase sensitive detection capability. The signals due tothe periodicity of the fringe pattern have random phase for eachparticle. So the other advantage of the frequency shifter is that theheterodyne signal will have a known phase (same as the frequencyshifter), which could allow for phase sensitive detection (lock inamplifier). As shown before, the signals from this system will consistof a sinusoidal signal with an envelope function from a particle'spassage through the intensity profile of the fringe pattern. So all ofthe techniques described previously for processing these signals can beapplied to this case. In this case, the scattered signal, at eachposition on the detector array, is the square root of the product of thescattered intensities from each of the crossed light beams. Hence thescattered light intensities, from a particular position on the detectorarray, in the simultaneous equations shown previously, must be replacedwith the square root of the product of the scattered intensities fromeach of the crossed light beams at the scattering angle from each beamfor that same detector array position.

The method shown in FIG. 97 could also be implemented using the opticalsystem in FIG. 78, by placing a periodic mask in the plane of aperture7801 in FIG. 78. The image of this mask in the sample cell would providea periodic intensity profile which would modulate the scatter signalfrom a particle passing through the intensity profile. The mask couldhave a sinusoidal or square wave transmission profile as shown in asingle section of the mask in FIG. 66 (for example). The mask could alsobe fabricated with a Barker code or other code which has a very sharpautocorrelation function to use correlation between detector signals(also see below). However, in this case the scattering signals are notthe square root of the product of scattering signals from two differentscattering angles. The signal is only from the actual scattering anglesrelative to the incident beam as defined before for detector array 7821or detector array 7822.

In both FIGS. 96 and 97, the system can be designed to provide beatsignals on all detector elements with nearly the same phase andfrequency. Hence high level signals can be multiplied times lower levelsignals to retrieve the lower level signals from noise. This method canalso be used with the system shown in FIG. 78, where each particleproduces a single pulse. The integral of the product of the largestscatter signal with a smaller signal, which needs to be recovered fromthe noise, will improve the signal to noise of the integral over thepulse for that smaller signal. This could also be accomplished by onlyintegrating the lower signal while the larger signal is above somethreshold, as described previously. This method will also work forsignals which are not modulated. The integral of the product of singlepulses will also improve the signal to noise of lower level signals whenmultiplied by higher level signals which have the same pulse shape. Thiscould be accomplished with the following equation which calculates amore accurate estimate to the integral of S2 by using correlation with ahigher level signal of the same functional shape (single pulse,amplitude modulated heterodyne signal, etc.):

S2I=INT(S1.*S2,t1,t2)/INT(S1,t1,t2)

Where S1 is the high level signal and S2 is the low level signal whichhas high correlation to S1. And t1 and t2 are the start and stop timesof the particle scatter pulse. The value of INT(S1.*S2, t1,t2) could beused directly, without normalization, in simultaneous equations, lookuptables, or search models as long as the theoretical model is calculatedfor INT(S1.*S2, t1,t2).

In both FIGS. 96 and 97, the detector arrays can be replaced by opticarrays as shown in FIGS. 79, 80, 81, 83, 84, and 86, for example. Theseoptic arrays can be configured in a detection system as shown in FIGS.82, 85, and 87, for example.

Consider two optical systems, AA and BB. Any detector system in systemAA using an aperture, which is in the image plane of the particle, canbe used in any other system BB by placing that aperture at anappropriate image plane of the particles in system BB, along with thedetection system from system AA. For example, the detector subsystem ofpinhole 7411, lens 7404, lens 7405, beam splitter 7431, multi-elementdetector array A and B in FIG. 74 could replace aperture 7802 anddetector array 7821 in FIG. 78. Other examples are replacing theaperture 9341 and aperture 9342 systems in FIG. 93, or the aperture 5202system in FIG. 52, or the pinhole 7411 system in FIG. 74, with any ofthe systems shown in FIG. 82, 85, or 87. Also any methods used by systemAA, which defines interaction volumes by using apertures and whichmeasures scattered light in multiple angular ranges, can be used in anyother system BB, which also defines interaction volumes by usingapertures and which measures scattered light in multiple angular ranges.For example, the methods used for FIGS. 1, 2, 2 a, and 37 can be appliedto the system in FIG. 78, whose apertures 7802 and 7803 behave in asimilar fashion to slits 114 and 115 in FIG. 1 or apertures 3711 and3712 in FIG. 37.

In many cases, the light intensity, illuminating the particles, must beincreased by focusing the source light beam to provide sufficientscatter signals. In all scattering systems with a collimated lightsource, the collimated light beam may be replaced by a focused lightbeam. However, the scatter detectors must not receive light from thisfocused beam in order to avoid large background signals which must besubtracted from the detector signals to produce the scatter portion ofthe signal. The source light beam should be blocked between the particlesample and the scatter detector. The most effective location for thislight block is in the back focal plane of the lens which collects thescattered light. Examples of this plane are the planes of annularspatial filters in FIGS. 14, 15 and 41, the source blocks in FIGS. 49,49B, 51, and the light block in FIG. 68. The central light block atthese planes must be of proper size to block the direct source lightfrom the beam, but also pass the scattered light at scattering angleswhich are higher than the highest angle of the diverging source lightbeam rays, after the beam focus.

All drawings of optical systems in this disclosure are for illustrativepurposes and do not necessarily describe the actual size of lensapertures, lens surface shapes, lens designs, lens numerical apertures,and beam divergences. All lens and mirror designs should be optimizedfor their optical conjugates and design requirements of that opticalsystem using known lens and mirror design methods. Any single lens canbe replaced by an equivalent multi-lens system which may provide loweraberrations. The drawings are designed to describe the concept; and sosome beam divergences are exaggerated in order to clearly show beamfocal planes and image planes within the optical system. If thesedrawings were made to scale, certain aspects of the invention could notbe illustrated. And in particular, the source beam divergence half anglemust be smaller than the lowest scattering angle which will be measuredfrom particles in that beam. For low scattering angles (largerparticles) the source beam would have a very small divergence angle,which could not be seen on the drawing.

Also in this disclosure, where ever an aperture is used to passscattered light and that aperture is in an image plane of the scatteringparticle, a lens can be placed between the detector(s) (or optic array)and that aperture to reduce smearing of the scattering pattern due tothe finite size of the aperture. The detectors could be placed in theback focal plane of said lens, where each point in the focal planecorresponds to the same scattering angle from any point in theinteraction volume. The detector(s) (or optic array) would be placed inthe back focal plane of said lens to effectively place the detector atinfinity, where the angular smearing is negligible, as shown anddiscussed in FIG. 24. Conversely, in some single particle counting casesand cases with a very small interaction volume, where the detector isplaced in the back focal plane of a lens, that lens can be removed toallow the detector to see the scatter directly from the interactionvolume or from the aperture which is in the image plane of theinteraction volume, because the single scatterer is essentially a pointsource. However, in these cases the angular scale of the scatter patternat the plane of the detector may change; and the angular scale must bedetermined to theoretically model the scattering signals. In most cases,the angular scale is given by:

Scattering angle=arctangent(r/L)

Where r is the radius on the scattering detector or optic array and L isthe distance between the array and the aperture which is conjugate tothe particle. When the detector is in the back focal plane of a lens,then L is the lens focal length.

Also in this document, any use of the term “scattering angle” will referto a range of scattering angles about some mean scattering angle. Theangular range is chosen to optimize the performance of the measurementin each case. For example the use of the terms “low scattering angle” or“high scattering angle” refer to two different ranges of scatteringangles, because each detector measures scattered light over a certainrange of scattering angles

Note that all optic arrays described in this disclosure can beconstructed from segments of conventional spherical and asphericallenses, diffractive optics, binary optics, and Fresnel lenses.

Also the local signal baseline (local or close to the pulse in time)should be subtracted from most of the signals described in thisapplication because very small amounts of background scattered lightwill be detected from multiple scattering of particles outside of theinteraction volume. This background light will usually change over atime period which is longer than the pulse length from a particlepassing through the interaction volume, due to larger particles, whichpass outside of the interaction volume. As these larger particles passthrough any portion of the beam they create primary scatter which isrescattered from particles in the field of view of the detectors, butwhich are outside of the interaction volume. Since large numbers ofparticles may be involved, their scatter into the detectors may be equalto or larger than the scatter from the single particle in theinteraction volume. Therefore, both fluctuating and static backgroundscatter should be removed from the single particle scatter signal bybaseline subtraction. This subtraction could be accomplished by fittinga curve to the scattering signal, using only points before and after thesingle particle pulse. The values of this fitted curve in the region ofthe pulse would be subtracted from the signal to correct the pulsesignal for the added background. In most cases a linear fit will besufficient. Particle scatter signal pulses with large baseline levels orlarge changes in baseline across the pulse, can be eliminated from theparticle count due to inaccurate baseline correction. This problem ofmultiple scattering is also mitigated by the concept, shown in FIG. 48and FIG. 104, which eliminates most of the scattered light fromparticles outside of the interaction volume, reducing the secondaryscatter from these particles and other particles in the detector's fieldof view. Both of these figures show the crossection of optical elements(transparent cones) which are symmetrical about the optical axis of thelight source. In FIG. 104, the inner and outer surfaces of each cone areconcave spherical surfaces, with centers of curvature at the beam focusor interaction volume, to reduce reflection at high scattering anglesand to prevent shift of beam focus and viewing volume due to any changein the refractive index of the dispersant. In FIG. 104, both theincident beam and scattered light pass through the cones, in both theforward or backward directions. However, the cone angle could also bereduced to only contain the source light beam, leaving the scatteredlight to pass through the particle dispersion and exit the cell throughtransparent cell walls or spherical transparent cell walls with centerof curvature at the interaction volume. The flowing particle dispersionfills the entire volume (except for the cones) between the sample cellwall A and wall B. The cones displace the dispersant to createparticle-free volume between wall A and wall B. As shown before in FIG.48, the larger particles pass around the cones, while the smallerparticles, of interest to the cone scattering detectors, can passthrough the gap between the cones. This design will provide substantialreduction of background scatter from other particles and provide stablebaselines for detection of low level pulses from small particles. Thecones could also be constructed from hollow cones with spherical windowson each end, but this would probably be more expensive than a solid conewhich can be molded as one piece in glass or plastic. This idea couldalso be designed for use in one scattering plane without the symmetryabout the optical axis of the light source and particle flow into thepage on FIG. 104. In this case each truncated cone would become atruncated wedge.

Ensemble particle size measuring systems gather data from a large groupof particles and then invert the scattering information from the largeparticle group to determine the particle size distribution. This scatterdata usually consists of a scatter signal vs. time (dynamic scattering)or scatter signal vs. scattering angle (static scattering). The data iscollected in data sets, which are then combined into a single largerdata record for processing and inversion to produce the particle sizedistribution. Inversion techniques such as deconvolution and searchroutines have been used. The data set for dynamic light scatteringconsists of a digital record of the detector signal over a certain time,perhaps 1 second. The power spectra or autocorrelation functions of thedata sets are usually combined to produce the combined input to theinversion algorithm for dynamic light scattering to invert the powerspectrum or autocorrelation function into a particle size distribution.Also the data sets can be combined by concatenation, or by windowing andconcatenation, to produce longer data sets prior to power spectrumestimation or autocorrelation. Then these power spectra orautocorrelation functions are averaged (the values at each frequency ordelay are averaged over the data sets) to produce a single function forinversion to particle size. Like wise for angular scattering, theangular scatter signals from multiple detectors are integrated over ashort interval. These angular scattering data sets are combined bysimply averaging data values at each scattering angle over multiple datasets.

Since the inverse problem for these systems is usually ill-conditioned,detecting small amounts of large particles mixed in a sample of smallerparticles may be difficult because all of the particle signals from theparticle sample are inverted as one signal set. If the signals, fromonly a few larger particles, is mixed with the signals from all of theother smaller particles, the total large particle scatter signal may beless than 0.01 percent of the total and be lost in the inversionprocess. However, in the single short data set which contained thelarger particle's scattered light, the larger particle scatter may makeup 50% to 90% of the total signal. The larger particle will easily bedetected during inversion of these individual data sets.

Users of these systems usually want to detect small numbers of largeparticles in a much larger number of smaller particles, because theselarger particles cause problems in the use of the particle sample. Forexample, in lens polishing slurries, only a few larger particles candamage the optical surface during the polishing process. In most casesthese larger particles represent a very small fraction of the sample ona number basis. Therefore, if many signal sets (a digitized signal vs.time for dynamic scattering or digitized signal vs. scattering angle forstatic scattering) are collected, only a few sets will include anyscattered signals from larger particles. An algorithm could sort out allof the data sets which contain signals from larger particles and invertthem separately, in groups, to produce multiple size distributions,which are then weighted by their total signal time and then combined toform the total particle size distribution. The data sets may also besorted into groups of similar characteristics, and then each group isinverted separately to produce multiple size distributions, which arethen weighted by their total signal time and then summed over each sizechannel to form the total particle size distribution. In this way, thelarger particles are found easily and the smaller particle data sets arenot distorted by scatter signals from the larger particles. Even if allof the signals for large particles over the full data collection time isless than 1% of the total signal, including large and small particles,this small amount would be inverted separately and the resultingdistribution would be added to the rest of the size distribution withthe proper relative particle volume percentage.

This technique works better when many short pieces of data are analyzedseparately, because then the best discrimination and detection ofparticles is obtained. However, this also requires much pre-inversionanalysis of a large number of data sets. The key is that these data setscan be categorized with very little analysis. In the case of angularlight scattering, comparison of signal values from a few scatteringangles from each signal set is sufficient to determine which signal setsinclude signals from larger particles or have specific characteristics.In the case of dynamic light scattering, the spectral power in certainfrequency bands, as measured by fast Fourier transform of the data setor by analog electronic bandpass filters could be used to categorizedata sets. Consider a dynamic scattering system where the scatteringsignal from the detector (in heterodyne or homodyne mode) is digitizedby an analog to digital converter for presentation to a computerinversion algorithm. In addition, the signal is connected to multipleanalog filters and RMS circuits, which are sequentially sampled by theanalog to digital converter to append each digitized data set withvalues of total power in certain appropriate frequency bands whichprovide optimal discrimination for larger particles. The use of analogfilters may shorten the characterization process when compared to thecomputation of the Fourier transform. These frequency band power valuesare then used to sort the data sets into groups of similarcharacteristics. Since larger particles will usually produce a largesignal pulse, both signal amplitude and/or frequency characteristics canbe used to sort the data sets. The total data from each formed group isthen processed and inverted separately from each of the other groups toproduce an individual particle size distribution. These particle sizedistributions are summed together after each distribution is weighted bythe total time of the data collected for the corresponding group.

The use of analog filters is only critical when the computer speed isnot sufficient to calculate the power spectrum of each data set.Otherwise the power spectra could be calculated from each data setfirst, and then the power values in appropriate frequency bands, asdetermined from the computed power spectrum, could be used to sort thespectra into groups before the total data from each group is thenprocessed and inverted separately to produce an individual particle sizedistribution. For example the ratio of the power in two differentfrequency bands can indicate the presence of large particles. Theresulting particle size distributions are summed together after eachdistribution is weighted by the total time of the data collected for thecorresponding group. This process could also be accomplished using theautocorrelation function instead of the power spectrum of the scattersignal. Then the frequency would be replaced by time delay of theautocorrelation function and different bands of time delay would beanalyzed to sort the data sets before creating data groups.

In angular scattering, a group of detectors measure scattered light fromthe particles over a different angular range for each detector. Thesedetector signals are integrated over a certain measurement interval andthen the integrals are sampled by multiplexer and an analog to digitalconverter. In this case, the angular scattering values at appropriateangles, which show optimal discrimination for larger particles, could beused to sort the angular scattering data sets into groups before thetotal data from each group is then processed and inverted separately toproduce an individual particle size distribution for that group. Theseresulting particle size distributions are summed together after eachdistribution is weighted by the total time of the data collected for thecorresponding group.

These sorting techniques can also be used to eliminate certain data setsfrom any data set group which is inverted to produce the particle sizedistribution. For example, in dynamic scattering, very large particlesmay occasionally pass through the interaction volume of the opticalsystem and produce a large signal with non-Brownian characteristicswhich would distort the results for the data set group to which thisdefective data set would be added. Large particles, which are outside ofthe instrument size range, may also cause errors in the inverted sizedistribution for smaller particles when their data sets are combined.Also vibration or external noise sources may be present only duringsmall portions of the data collection. These contaminated data setscould be identified and discarded, before being combined with the restof the data. Therefore, such defective data sets should be rejected andnot added to any group. This method would also be useful in conventionaldynamic light scattering systems, where multiple groups are not used, toremove bad data sets from the final grouped data which is inverted. Bybreaking the entire data record into small segments and sorting eachsegment, the bad data segments can be found and discarded prior tocombination of the data into power spectra or autocorrelation functionsand final data inversion. This method would also be useful in staticangular scattering to eliminate data sets from particles which areoutside of the instrument size range.

In some cases, a large number of categories for sorted groups areappropriate to obtain optimal separation and characterization of theparticle sample. The number of categories is only limited by thecumulated inversion time for all of the sorted groups. The totalinversion time may become too long for a large number of groups, becausea separate inversion must be done for each group. However, after theinformation is sorted, abbreviated inversion techniques may be usedbecause the high accuracy of size distribution tails would not berequired to obtain high accuracy in the final combined particle sizedistribution. In many cases, only two groups are necessary to separateout the largest particles or to eliminate defective data sets.

This disclosure claims sorting of data sets for any characteristics ofinterest (not only large particles) and for any applications where largedata sets can be broken up into smaller segments and sorted prior toindividual analysis or inversion of each individual set. Then theresulting distributions are combined to create the final result. Thisincludes applications outside of particle size measurement.

Another application is Zeta potential measurement. Low scattering anglesare desirable in measurement of mobility of particles to reduce theDoppler broadening due to Brownian motion. However, large particlesscatter much more at small angles than small particles do; and so thescatter from any debris in the sample will swamp the Doppler signal fromthe motion of the smaller charged particles in the electric field. Thisinventor has disclosed methods of measuring Dynamic light scatteringfrom small interaction volumes created by restricting the size of theilluminating beam and the effective viewing volume. When only scatteredlight from a very small sample volume is measured, the scatter fromlarge dust particles will be very intermittent, due to their small countper unit volume. So the techniques outlined above can be used toeliminate the portions of the signal vs. time record which contain largesignal bursts due to passage of a large particle. In this way, Zetapotential measurements can be made at low scattering angles without thescattering interference from dust contaminants.

In optical systems which need to count very small particles, lightsources with shorter wavelengths may be preferred due to the higherscattering efficiencies (or scattering crossections) at shorterwavelengths.

The alignment of angular scattering systems can drift due to drift ofthe source beam position or changes in the wedge between the sample cellwindows. FIG. 100 shows an optical system which measures angularscattering distribution from a particle dispersion in a sample cell. Theangular scattering distribution is used to determine the sizedistribution of the particles. If the optical wedge between the samplecell windows changes or if the dispersant refractive index is changed,the system will go out of alignment due to refraction in the opticalwedge. The laser focus spot will move to another position on thedetector array, saturating detector elements which should be measuringscattered light only. This invention uses a retroreflector and asource-detector module to provide stable alignment against the driftsources described above. Lens 10001, pinhole, and lens 10002 form aspatial filter. The light beam from this spatial filter passes throughthe sample cell and dispersion. The beam and scattered light are thenretroreflected back through the same sample cell, where more scatteroccurs on the second pass. All of the scattered light is collected bylens 10003, which focuses it onto a detector array in the back focalplane of lens 10003. As long as the components are rigidly mounted to acommon base in the source-detector module, the system will maintainalignment after initial alignment at the factory. After initialalignment, this system will maintain alignment over a large range ofbeam alignment drift, dispersant refractive index change, or sample cellwedge drift. If the sample cell drift or dispersant refractive indexdrift are not problems, the optics can be arranged so that the beambetween lens 10002 and the retroreflector does not pass through thesample cell, while the beam does pass through the sample cell betweenthe retroreflector and lens 10003.

In most of the optical systems described in this application, certainranges of angular scattered light are measured separately. Usually twoangular ranges will only provide high particle dimension sensitivityover a limited size range. The following methods can be used to extendthe size range of the detection systems:

1) many detectors in each scattering plane2) many lens/multi-detector systems, with different scattering angleranges, multiplexed into a single optical system using beam splitters.3) One lens in the scatter path has adjustable focal length (such as azoom lens) to measure the scattering pattern at various angular scalefactors (scattering angle vs. radius on the detector array)4) With no lens between the particle image plane aperture and thedetector array (for example aperture 7802 and detector array 7821 inFIG. 78) the angular scale factor of the detector array or optic arrayis adjusted by changing the distance between the aperture and thedetector array. The angular extent of the detector array is inverselyproportional to that distance.5) Case 3 or 4 with the focal length or distance adjustment based upon:size range known by user or the counted size distribution from the firstgroup of particles counted. The user or computer controller could alsochoose different scattering angular scale factors (by changing the lensfocal length or the moving the detector) for each of a group ofsequential counting sessions on the same particle sample and then inverteach of these data sets separately, using the proper angular scalefactor for each set. Then the resulting size distributions are combinedinto one size distribution.

In cases where a 2-dimensional detector array is in the image plane ofthe particles, that 2-dimensional array can be replaced by a1-dimensional array which repeatedly scans across the interaction volumeas the particles flow through that volume in a direction perpendicularto the long dimension of that array (the direction between adjacentpixels). Essentially the same information as obtained with the2-dimensional array can be obtained sequentially on the 1-dimensionalarray because the other perpendicular dimension is provided by theparticle motion. The two dimensional “virtual pixel” distribution ofscattered signals is reconstructed by combining these sequential1-dimensional scans, based upon the flow velocity. And as before,contiguous particle pixels (virtual pixels with signals indicative of aparticle) are combined to produce scattering signals for each particle,as described previously for FIGS. 11, 12, and 14.

In all cases shown in this application, all possible polarizations andwavelengths of the source and all polarization and wavelength selectionsof the detection system can be employed. Each Fij in the previousanalysis can have a specific light polarization and wavelength whichoptimizes the accuracy of the particle characterization. Any combinationwill provide size and shape information. However, the theoreticalscattering model must accurately describe the wavelength andpolarization state of the source and the polarization and wavelengthselection of the detector. Polarization and wavelength effects can beused to determine particle size and shape using the search oroptimization methods described previously. Below is a list of the bestconfigurations for detection of size and shape using polarizationeffects in the optical systems described in this application:

Any source can be polarized in a particular direction. Any detectionsystem can select any polarization, including the polarizations paralleland perpendicular to that source polarization direction. For example twoorthogonal polarizations can be selected by a polarizing beamsplitterwhich splits the scattered light into two separated scattering detectionsystems. Each of these detectors can consist of any detection systemdescribed previously in this application. Also each scattering planesegment in a detection array, such as shown in FIG. 84, could be coveredby a polarizing material with polarization orientation parallel orperpendicular to the scattering plane to provide multiple polarizationsfor each particle count. The scattered flux passing through each segmentwill have a theoretical dependence upon the size and shape of theparticle. As before, simultaneous equations can be formed as functionsof these flux values to solve for unknown size and shape parameters. Tosave computation time per particle, each of these equations should be aparameterized into a simple function which is fit to the actual computedflux values which are obtained from Fraunhofer theory (withoutpolarization information) or known polarization methods, such asT-matrix and Discrete Dipole Approximation, (see “Light Scattering byNonspherical Particles”, M. Mishchenko, et al.). These methods areusually very computationally demanding. However, the theoretical resultsfrom these demanding methods can be fit to simple functions (such aspolynomial or power series) of the particle size and shape, usingregression analysis of computed data. And when closed form solutions areavailable, the simultaneous equations can be formed directly from theclosed form solutions or from less computationally demanding closed formapproximations (using said function fitting methods) of the full closedform solution. The only requirement is that the theory be capable ofdescribing the scatter from particles of the sizes and shapes ofinterest and with the source polarization and polarization selection ofthe detection system. Once the simplified simultaneous equations areformed, the optimal inversion technique can be chosen from among thevarious search, regression, and optimization algorithms available. Inmany cases, the simultaneous equations can be posed as a functionalminimization problem which is amenable to many of the minimizationalgorithms. The RMS error between the theoretical flux output of thesimultaneous equations for a given set of particle parameters (forexample, particle dimensions) and the actual measured signal values cancreate a function to be minimized by various minimization algorithms asdescribed previously.

[S,f(S),R]=M(P,O)

The set of signal values S (flux signal peak, integral, etc.), otherfunctions of S (f(S)), and ratios, R, of signal values are a function Mof the particle parameters, P, (dimensions, size, shape, etc.). M isalso a function of the descriptors, O, of the optical system such asscattering plane orientations, scattering angles, polarization statesand wavelengths of the sources, and polarization selections of thedetectors. M may include a set of simultaneous equations (linear ornonlinear), an integral equation such as a convolution, or a singleequation. M is determined from known scattering theory based upon theoptical system O and the range of parameters P. M should be simplifiedby the methods described above to reduce computation time. In somecases, M can be directly inverted to Minv to produce P as a function ofS, f(S), and R.

P=Minv(O,S,f(S),R)

In other cases, where explicit inversion of M is not possible, search,function minimization, or optimization methods should be employed tominimize an error function, such as E:

E=SQRT(SUMi((Smeasi−Sti)̂2)+SUMi((Rmeasi−Rti)̂2+SUMi((f(S)measi−f(S)ti)̂2))

These may include iterative methods. Where Smeasi is the value measuredfor the ith signal and Sti is the theoretical value for the ith signalbased on the estimate for P; and where Rmeasi is the signal ratio valuemeasured for the ith signal ratio and Rti is the theoretical ratio valuefor the ith signal ratio based on the estimate for P; and wheref(S)measi is the signal function value measured for the ith signalfunction and f(S)ti is the theoretical signal function value for the ithsignal function based on the estimate for P. The algorithms are designedto refine this P estimate using iterative procedures to find theestimated P values which minimize the error E. These algorithms includeNewton's method, Levenburg Marquardt method, Davidon-Fletcher-Powell,constrained and unconstrained optimization methods, global searchalgorithms, etc. All of these methods will minimize E, by using M tocalculate Sti, f(S)ti, and Rti for each new estimate of P. Thisminimization is performed individually for each particle to determinethe size and shape parameters for that particle. In some cases, thisinversion process will use a certain conceptual form for the propertiesof M, such as the 2-dimensional structure in FIG. 27, which providesboth elimination of counted signal events, which do not meet therequirements to be particles, and a means for deconvolution or inversionof the remaining counted signal events.

In general we can define a Sv vector which consists of all of themeasured quantities and a Pv vector which consists of all of theparticle characteristics, which are to be determined from Sv:

Sv=[S1, S2, S3, . . . , R1, R2, R3, . . . f1(S1, S2, S3 . . . ),f2(S1,S2, S3 . . . ),f3(S1, S2, S3 . . . )]

Pv=[P1, P2, P3 . . . ]

Where Si are scatter signals (flux signal peak, integral, etc.), Ri areratios of different Si values, and fi are other functions of the Sivalues. The Pv vector consists of particle characteristic values, suchas particle major axis length, particle aspect ratio, and particleorientation, for example. Then the optical model M is the transformoperator between these two vectors:

Sv=M(Pv)

M is a function of the optical configuration descriptor, O, whichincludes the scattering plane orientations, scattering angles,polarization states and wavelengths of the sources, and polarizationselections of the detectors. The M function is determined fromtheoretical scattering calculations such as Mie theory or T-matrix andDiscrete Dipole Approximation, (see “Light Scattering by NonsphericalParticles”, M. Mishchenko, et al.). This M function can be approximatedby regression analysis of the scattering value results from thesescattering calculations. An example of this regression is shown belowfor 2 Pv parameters for polynomial regression:

Svj=SUMi[Aij(Oj,P2)*(P1̂i)]

Aij=SUMk[Bijk(Oj)*(P2̂i)]

Where Oj is the optical system descriptor for signal Svj and A is thepower operator. The regression analysis of scattering results from thetheoretical scattering calculations produces the coefficients, Aij andBijk. This technique can be extended to more than 2 elements in Pv, byproviding more layers of coefficients. These equations, or the moregeneral solution equations for M(Pv) shown above, are solved iterativelyby finding the values in Pv which minimize the error Err:

Err=SUMj((Svej−Svmj)̂2)

Where Svmj are the measured values of Svj; and Svej are the calculatedvalues, in vector Sve, for the current iteration estimate for Pve(Sve=M(Pve)). The optimization methods, described above, are used toiteratively change the values in Pve to lower and minimize Err. Then thebest Pv is equal to Pve, when Err(Pve) is minimum. This iterativeprocess may consume excessive time, when required for each countedparticle. Depending upon the available computer resources, directinversion of M may be preferred. In some cases, the operator M can beinverted directly. For example, the regression analysis could switch thevariables in the regression approximation equations to solve for Pv:

Pj=SUMi[Cij(Oj,S2)*(Sv1̂i)]

Aij=SUMk[Dijk(Oj)*(Sv2̂i)]

The regression analysis of scattering results from the theoreticalscattering calculations produces the coefficients, Cij and Dijk andcreates the inverse operator Minv. Then Pv is directly calculated fromSv:

Pv=Minv(Sv)

The use of polynomial regression is just one example of reducing scatterresults from very computationally intensive algorithms (such as Mie,T-matrix, or Discrete Dipole Approximation) to simple equations whichcan be computed in a fraction of a second instead of minutes. Ingeneral, other types of regression functions, such as Bessel functions,may be more appropriate.

The optical system, O, must be designed to produce Sv which has largesensitivity to Pv. The scattering plane orientations, scattering angles,polarization states and wavelengths of the sources, and polarizationselections of the detectors must be chosen to maximize this sensitivityto avoid ill-conditioning of the equation set Pv=Minv(Sv).

Also in some cases, the discrete values in the data sets (Svd and Pvd)from the theoretical scattering calculations can be used to create adiscrete multi-dimensional function set which can be searched inmulti-dimensional space:

Svd=M(Pvd)

Find the discrete values Pvd, by search and interpolation of themulti-dimensional data set, which produce Svd values which agree withSvm values to minimize Errd.

Errd=SUMj((Svdj−Svmj)̂2)

The same analysis, as described for polarization properties, can be usedfor different source or detection wavelengths, which also determine thesystem response to particle characteristics. Optical filters in thedetection system and various source wavelengths are used. Andappropriate scattering models are used to describe the effects ofwavelength on the scattering pattern. In many cases, the angular scaleof the scattering distribution scales approximately inversely withwavelength. Any point in the angular scattering distribution movestoward higher scattering angle as the wavelength is decreased.Therefore, use of different wavelengths for Fij, can provide additionalinformation for particle characteristics. For example, the Mieresonances respond to wavelength changes differently than thenon-resonating portion of the scattering distribution, providing a meansfor better correction of Mie resonance induced errors.

Also in any system described previously, the flow velocity could belowered for smaller particles to increase their residence time in theinteraction volume, providing longer signal period and better signal tonoise. Also most of these techniques do not require the dispersant to bea liquid. These techniques are also claimed for measuring the size andshape of particles dispersed in a gas or aerosol. The same flowingconditions can be produced by pumping the gas aerosol in a closed loopthrough the optical system, or by pumping or settling the aerosol in asingle pass through the optical system.

If absolute signal values are used instead of signal ratios, the singlesize response will be broader in the multi-dimensional space and thedeconvolution problem will be more ill-conditioned. However, this can bethe best choice for very small particles where the absolute signals willhave much higher particle size sensitivity than the signal ratios.

This application claims any combination of the apparatus and methodsdescribed in this application to extend the size range of the totalsystem. These methods may also be combined with conventional directimaging systems to size larger particles.

When more than one particle is present in the interaction volume,particle size errors can occur. Many of the systems and methodsdescribed in this application reduce the probability of countingcoincident particles by providing interaction volumes of various sizes,such as shown in FIG. 41, where a set of apertures define various sizedinteraction volumes in the sample cell. The concept shown in FIG. 93could also be used to define multiple interaction volumes, where eachinteraction volume has a separate light source. This may have someadvantages over the system in FIG. 41 in producing source focal spotswith maximum intensity in the sample cell. FIG. 14 uses a 2-dimensionaldetector array to define multiple interaction volumes. Multiple sizedsource spots could also be used to define multiple interaction volumesin FIG. 78, by using the source beamsplitter system in FIG. 93 in FIG.78. These interaction volumes (source spots) could be coincident in thesample cell and each one could be selected by sequentially turning eachsource on and collecting scatter from that source, while many particlespass through the beam. The particle concentration is reduced (perhaps insteps) by a system as shown in FIG. 13 to reduce the counting ofcoincident particles to an acceptable level. However, for broad sizedistributions, single particle counting is difficult to achieve in thelarger interaction volumes where many small particles may be presentwith each large particle. In this case, very low angle scattering can bemeasured. Since low angle scattering scales approximatelyproportionately to the fourth power of the particle diameter and thesmaller particle pulses will overlap, their scatter signal can beremoved from the larger particle pulses by baseline subtraction and/orpeak detection. This problem is also mitigated using the methods, shownin FIGS. 71, 72, and 73, which allow overlapping pulses to be measuredseparately.

FIG. 88 a shows the actual total count distribution and the measuredcount distributions from two different sized interaction volumes, A andB. Interaction volume A, which detects smaller particles, is smallerthan interaction volume B. Therefore, interaction volume A can measureparticles at higher particle concentrations than interaction volume B.The count distribution will usually increase as the particle size, andS, decrease because usually there are many more smaller particles thanlarger particles. For both volumes A and B, the count distributions willbe limited to a certain range in S. The low signal detection limitaffects the lower S limit. And the upper limit is determined by thelargest particles which will produce a pulse, from which particle sizecan be determined for the size of the interaction volume. Particleswhich are larger than the interaction volume will not produce accuratepulses. Accurate single particle detection is maintained over theregions between A1 and A2 for interaction volume A, and between B1 andB2 for interaction volume B. These two regions should be contiguous orhave overlap to provide a continuous measured count distribution, whenthe count distributions from volumes A and B are combined to produce asingle count distribution. In the interaction region with the smallestparticles, the coincidence counts should be reduced by adjustment ofparticle concentration. The count distribution from that interactionvolume, A, can be used to correct the counts from the adjacentinteraction volume B, using the equations shown below. Then the Adistribution and corrected B distribution can be used to correct thedistribution from the next larger interaction volume C (not shown) andso on, until all of the count distributions are corrected forcoincidence counts. The techniques shown below can also be used tocorrect a single count distribution which covers the entire range of S.

In many cases described above, coincidence counts cannot be avoided andthe measured count distribution must be corrected for coincidencecounts. The count distribution N(S) is the number of events with signalcharacteristic S between S-deltaS and S+deltaS as a function of S. Asbefore, S can be any of the signal characteristics (such as scattersignal peak or integral) or some functions of these signalcharacteristics. Let Nm(S) be the measured count distribution whichcontains count errors due to coincidence counts. And let Nt be the truecount distribution without coincidence count errors. Then the followingrelationship can be formed:

Nm(Si)=SUM((SUM(Nt(Si+kSj)*Pk(Sj)),j=1,j=nns),k=1,k=nnk) for i=1 to Nsi

Where Pk(S) is the probability that k particles, with characteristic S,will be present coincidentally in the interaction volume used to measurecharacteristic S. This probability is derived from the Poissonprobability distribution using the average number (Na) of particles ofsignal characteristic S present in the interaction volume during asingle data collection or at the point of data sampling (signal peak orintegral measurement for example).

Pk(S)=EXP(−Na)*((Na)̂k)/k!=EXP(−Nt(S))*((Nt(S))̂k)/k!

where EXP is the exponential function and * is multiply operation

The equations for Nm(Si) form a set of Nsi simultaneous equations whichcan be solved for Nt(Si), given Nm(Si) and Pk(Si). The value nns is thetotal number of counting channels, each with a different center Sjvalue. The value nnk is the maximum number of coincident particles inthe interaction volume for a particle which produces signal Sj. Thevalue of nnk depends upon the particle concentration for each value ofSj. The value nnk may be limited to the point where Pk(S) (for k=nnk)becomes negligible or to the point where baseline correction effectivelyremoves the signal due to the coincident particles of signal Sj. Theseequations are solved by many different types of algorithms includingiterative processes such as function minimization or optimizationalgorithms (global search, Newton's method, Levenburg-Marquardt method,etc.). The values of Nt can be constrained to be positive, usingconstrained optimization methods to improve accuracy. The iterativeprocess could start with an estimate for Nt(S), called Nte(S). Then,using iterative optimization methods, the values in Nte(S) are changed,during each iteration, to produce a new estimated Nm(S) function, calledNme(S), (calculated from the equation below) which fits better to theactual measured values of Nm(S). This iterative process is continueduntil the error, Em, is minimized. The values of Nte(S) at minimum Emare the final values for the count distribution without coincidencecounts. Nm(S) are the actual measured values.

Nme(Si)=SUM((SUM(Nte(Si+kSj)*Pk(Sj)),j=1,j=nns),k=1,k=nnk) for i=1 toNsi

Em=SQRT(SUMi((Nm(Si)−Nme(Si))̂2))

In general, the coincidence counts are best removed from the count datausing the methods described for FIGS. 26, 27, 28, 61, and 62, which showthe 2-dimensional case of a multi-dimensional concept. Themulti-dimensional analysis creates a function of multiple variables of S(or functions of S). Typically each variable is measured from adifferent scattering angle range, different scattering plane, differentlight polarization, different light wavelength or a function of thesedifferent variables. In any case, the function for a system, without anybroadening mechanisms, will be a nonlinear line (or path) whichtraverses the multi-dimensional space. Each point along this line (orpath) corresponds to a different value of the particle characteristic orsize. When broadening mechanisms are added, a probability distributionfor existence of a particle is created around this line inmulti-dimensional space. Detected events, which are too far from thisideal line or in the regions of low probability, are rejected and notadded to the count. The distance of a count event location from thisideal line, and corresponding probability of event acceptance, isdetermined by an algorithm using analytical geometry relationships forthe multi-dimensional space. Any single particle will have a certainnominal combination of S values or S function values (one for eachdimension of the space). If a second particle is coincident with thatsingle particle, the S values or S function values from that particlepair will usually not be within the acceptable region of the space andcan be rejected. This rejection process is improved by reducing thebroadening mechanisms, which create a wider region of acceptance in themulti-dimensional space. For example, use of an apodized or truncatedbeam, to provide better intensity uniformity of the source in theinteraction volume, will reduce this broadening source and reduce theregion of acceptance around the ideal line in multi-dimensional space.Then the coincidence count rejection will be much more effective. Theacceptance region in the multi-dimensional space can also be determinedfrom the region which is most populated by events, if the particleconcentration is low so that coincidences are rare. In this case,outliers of the multi-dimensional distribution are rejected.

Application PCT/US2005/007308 (Application 1) is a basis document forthis application. The term Application 1 also includes updates made toPCT/US2005/007308, which are included in this application. The particlecounting optical systems, including those described previously by thisinventor, can measure and count particles on microscope slides or othersubstrates (windows for example), without flowing particles through theinteraction volume. The interaction volume is the volume of particledispersion from which scatter detectors can receive scattered light fromthe particles. The interaction volume is the intersection of theparticle dispersion volume, the incident light beam, and viewing volumeof the detector system. These substrates can include particles dispersedon microscope slides (with and without cover slips) or a particledispersion sandwiched in a thin layer between two optical windows. Usingthis method, the thickness of the sample volume is reduced, reducing thebackground scatter from other particles, in the sample, which areilluminated by the source beam or scattered light from other particles.The counting process is accomplished by moving the substrate, upon whichthe particles are dispersed, so that the optical system can view variousspots or interaction volumes on that substrate and measure any particlesthat are present at each location. Essentially the moving substrateprovides the particle motion which is provided by the dispersion flow inthe flowing systems described previously by this inventor. This motioncan also provide the Doppler shift required for some of the heterodynedetection systems described previously by this inventor. Either theoptical system or the substrate (or both) can be moved so that theinteraction volume of the optical system is scanned across the substrateto sample continuous scatter signals during the motion or to interrogateindividual sites for particles. This scan can consist of any profile(zig-zag, serpentine, spiral etc.) which will efficiently interrogate alarge portion of the substrate surface. The scan could also be stoppedat various locations to collect scattering signal over a longer periodwith improved signal to noise.

The flow system shown in FIG. 107, uses two flow loops: flow loop 10702at high particle concentration and flow loop 10701 at the adjustableparticle concentration, as controlled by dispersion injections throughthe valve. The particle sample is introduced into the open sample vessel10712 in loop 10702 to be mixed with dispersant in flow loop 10702. Theflow velocity in either flow loop is sufficient to prevent settlinglosses of large particles and maintain a homogeneous dispersion. Thesample vessels provide access to the particle dispersion for introducingparticles to the loop; and they provide a means for removal of airbubbles, from the dispersion in the flow loop, which pass into theatmosphere. The arrows indicate the direction of the dispersion flowinto the top of each sample vessel. The injection of dispersion throughthe valve could also be injected directly into sample vessel 10711instead of the loop tubing. Also, the flow tube in each sample vesselcould end above the liquid level in the sample vessel, so that thedispersant falls through air before entering the fluid in the vessel.

In order to optimize the counting efficiency, the particle concentrationshould be increased to the maximum level, which will still allow a highprobability of single particle counting, without coincidences. In thisway, the largest number of particles will be counted in a given timeperiod, with very few coincidence counts. This is difficult toaccomplish on a substrate, such as a microscope slide, without usingtrial and error. Microscope slides and other substrates are difficult topopulate with particles in a repeatable manner, with predictableparticle concentration per unit area. The system, in FIG. 108, uses aflowing system, as shown in FIG. 107, to adjust the particleconcentration in a sample cell, with adjustable window separation. Thesystem consists of a sample cell housing, which consists of two cellhalves: sample cell housing 10801 and sample cell housing 10802. Thesecell housing halves can be moved relative to each other to providevarious cell window spacings. Each housing half contains a cell windowto pass the incident light beam and any scattered light from theparticles, as required by the optical system which measures scatteredlight from the particles in the sample cell. The sample cell in FIG. 108can be placed in the location of sample cell 10721 in FIG. 107. Theconduit on the inlet and outlet of the sample cell is flexible and thetwo sample cell halves are connected by flexible material, so that thesample cell halves can be moved relative to each other to change thespacing, between the windows, where the particles reside. The flexibleconduit, flexible connecting material, and two sample cell housinghalves provide a sealed chamber with window access for light, and inletand outlet access for flowing dispersion, while allowing for adjustmentof window spacing. This spacing is controlled by actuator(s) which moveone or both of the sample cell halves. The housing parts could bedesigned with O-ring seals, so that the windows can be removed from thehousing for cleaning. The windows could also reside in O-ring seals,which allow the window to slide though the O-ring seal to provide windowspacing adjustment, while providing a sealed chamber for the particledispersion.

The flowing system in FIG. 107 adjusts the concentration by monitoringthe particle count rate and injecting the proper amount of concentrateddispersion from flow loop 10702 into flow loop 10701, with the cellhousing in Position A, in FIG. 108. Position A provides a longer opticalpath through the particles than position B. Repeated injection andmeasuring steps may be needed to obtain an accurate concentration level.After the proper particle concentration is attained, the flow is turnedoff and the window spacing is reduced to trap a thin layer of particledispersion between the windows, as shown by Position B in FIG. 108. Thewindow spacing should be reduced slowly so that particles are notsegregated by particle size during the movement of dispersion from thecell. As dispersion is squeezed out of the gap between the windows, theability of particles to move with the dispersion may be particle sizedependent. If the dispersion moves slowly, particles of all sizes canfollow the dispersion as it is pushed out from between the windows,maintaining the original (Position A) particle size distribution betweenthe windows, when they are in Position B. The flow path of the cell andinternal window surfaces should be parallel to the gravitational force,so that larger particles do not settle onto the windows as the windowspacing is changed. During the window spacing changes, the particlesshould settle into the top of the cell and out of the bottom of cell,maintaining the size distribution. Once the final window spacing isreached (Position B), the cell housing could be tilted to orient theinner window surfaces to be perpendicular to the gravitational force toreduce settling motion of the particles during the scan. In position B,the optical system scans in a pattern (zig-zag, serpentine, spiral etc.)over that thin layer (in a plane parallel to the windows) to count theparticles in that layer. The interaction volume of the optical systemshould be maintained in the thin layer of dispersion, during the scan,by real time control of optical system focus or position of the opticalsystem along the optical axis, if needed. The window area should besufficient to hold the large number of particles needed to obtainaccurate count statistics and distributions. Otherwise, repeated steps,of Position A with flow, and then Position B with a counting session,may be needed to accumulate sufficient counts, by filling (Position A)the cell with a new sample of dispersion between each counting (PositionB) session. The windows are maintained at a larger separation (PositionA) while the concentration is being adjusted by injections of particledispersion from flow loop 10702 into flow loop 10701 through thecomputer controlled valve, with both loops flowing. The number ofparticles per unit volume and the largest particle size are measured, bythe optical system counting particles with flow on, during thisconcentration adjustment process. The concentration adjustment iscomplete (in position A) when the volume concentration is such that thepredicted particle number per unit area in the predicted thin layer(Position B) will be optimal (the largest number per area which willstill avoid significant levels of coincidence counts). This isdetermined from the measured number of particles per unit volume(determined from the particle count rate, the interaction volume sizeand the flow velocity) and the predicted thickness, of the thin layer,which can be determined to be some factor larger than the size of thelargest particle counted during the flow period. The thickness of thislayer could be controlled to be a certain percentage larger than thediameter of the largest counted particle to prevent crushing the largestparticles in position B. If the particle concentration is low, theoptimal thickness may be much larger than this minimum particle crushdistance in order to obtain sufficient particles per area for highparticle count rates. Also, a force sensor (as shown in FIG. 109) can beplaced between the actuator and the sample cell housing to determinewhen particles are being compressed, in order to stop the actuator fromreducing the window spacing further and crushing the largest particles.This force sensor feedback system can also stop the actuator when thetwo windows are in contact to prevent damage to the windows or theactuator. The window position adjustment also could be accomplished by asingle piece sample cell housing with an actuator movable window whichslides through an O-ring seal to adjust the window spacing. However,this option may require higher cost and maintenance. Also the flexibleconduit can take the form of a flexible diaphragm as shown in FIG. 109.As before, sample cell housing 10902 is moved by the actuator. Cellhousing 10902 is connected to the stationary sample cell housing 10902Bby a flexible diaphragm, which allows the sample cell housing 10902 andwindow 10912 to move relative to window 10911 to adjust the spacingbetween window 10912 and window 10911. The flexible diaphragm and twosample cell housing halves provide a sealed chamber with window accessfor light, and inlet and outlet access for flowing dispersion, whileallowing for adjustment of window spacing. The diaphragm and cellhousing 10902 are mounted on the face (see FIG. 110) of the sealed cellchamber which consists of cell housing 10901 and cell housing 10902B.FIG. 110 shows a frontal view (light source axis is perpendicular to thepage) of the cell and a top view A-A′ which shows the sides of thechamber which connect cell housing 10902B to cell housing 10901.

This adjustable sample cell concept can be used in any particle counter(including those described previously by this inventor) by replacing thesample cell in said system with this adjustable sample cell andproviding the hardware and software which will generate the informationfrom which the cell window spacing adjustment will be determined. Since,during the particle counting scan, movement of either the optical systemor sample cell (or both) may be provided by motor driven stages, theweight of these systems should be limited to avoid heavy accelerationloads on the stages. The optical system weight could be lowered by usinglaser diode or LED sources. Also the sample cell could be connected tothe flow system through long flexible tubes to allow motion of only thelight weight cell. If the velocity of the motor driven stage is too lowto obtain high particle count rates, the effective speed of the sourcespot in the thin particle layer can be increased by mounting the optics(or sample cell) on piezoelectric actuators and using linear motion ofthe stage. The piezoelectric actuators would quickly scan the sourcespot and collection optics in a short oscillating pattern perpendicularto the linear motion of the stage to produce a serpentine pattern acrossthe window with very high surface velocity. A single serpentine sweepacross the window covers a rectangular region with length equal to thetotal linear motion and width equal to the perpendicular oscillatingpattern motion. After each full single serpentine sweep, the stage ismoved so that the rectangular region of the next sweep is placedadjacent to the prior sweep region, by jumping over one sweeprectangular width in the direction perpendicular to the linear motion.The stage would travel back and forth across the entire window (steppingforward with each cycle) to move the fast oscillating source spot acrossthe entire area of window. The flow system in FIG. 107 is usually usedwhen particle concentration adjustment is required. Otherwise,lightweight substrates, such as microscope slides, can be used.

This concept can also be used in other types of scattering systems. Forexample, in ensemble angular scattering instruments (measuring scatteredlight from a group of particles), low particle concentration is requiredto avoid multiple scattering. But some users prefer to measure theparticle size of dispersions at higher particle concentration when theparticle size distribution is dependent upon the particle concentration.Multiple scattering occurs when the scattered light from a particle isscattered again by other particles, before being received by thedetector. Since the optical scatter model usually assumes only primaryscattered light, inversion of this multiple scattered light angulardistribution will produce errors in the calculated particle sizedistribution. Multiple scattering depends upon the total number ofparticles in the beam. Therefore, by reducing the pathlength of theincident light beam in the particle dispersion, multiple scattering canbe reduced to optimal levels, even at very high particle concentration.This pathlength adjustment could be accomplished under computer controlusing the sample cell shown in FIGS. 108 and 109. The light beamattenuation due to scatter, at the initial pathlength of measurement(Position A), could be used to calculate the appropriate pathlengthadjustment (Position B) to avoid significant multiple scattering. Thenthe sample cell window spacing is adjusted by the actuator(s) to providethis optimal window spacing (position B) and pathlength, before thefinal optical scatter measurement, which is inverted to produce theparticle size distribution. If the particle concentration is low, thewindow spacing at position B could be larger than the spacing atposition A to provide sufficient scattered intensity. The optimumspacing could also be determined by monitoring the angular scatteringdistribution or particle size distribution at various opticalpathlengths (window spacings) in the cell. Multiple scattering causesthe higher angle scatter to increase relative to the low angle scatter.Starting in position A, the scattering distribution (Distribution 1) ismeasured. Then the window spacing is reduced and the angular scatteringdistribution (Distribution 2) is measured again and compared to thedistribution (Distribution 1) measured at the prior spacing. If thechange (see DIFF below for example) in the shape of the distribution(for example the change in the ratio of low angle scatter to high anglescatter) is less than a certain threshold, then the multiple scatteringis negligible and Distribution 2 can be inverted to generate theparticle size distribution. If the change is larger than the threshold,then the multiple scattering was reduced by the spacing change and thespacing is reduced again to produce a new measurement of scatteringdistribution, Distribution 3. The shape of Distribution 3 is compared tothe shape of Distribution 2. If the difference (see DIFF below forexample) between the two shapes is less than the threshold, Distribution3 is inverted to create the particle size distribution. If the shapedifference is greater than that threshold, the window spacing is reducedagain to generate Distribution 4. This cycle is repeated until thedifference in shape between the scattering distributions measured at twosuccessive window spacings is less than the threshold. At this point,the multiple scattering is negligible because changes in dispersionpathlength have little effect on the shape of the angular scatteringdistribution. Then the distribution from this final spacing is invertedto produce the particle size distribution. This process could also beaccomplished by comparing the particle size distributions calculatedfrom the angular scattering distributions measured at successive windowspacings. Again the change in distribution shape a (ratio of largeparticle volume to small particle volume or DIFF function for example)is used to stop the process and accept the last size distribution. Theadvantage of using the particle size distribution is that the sizedistribution error due to multiple scattering is determined directlyfrom the difference between two successive distributions. However, thisprocess will take more computation time than comparing the scatteringdistributions, because an inversion of the scattering distribution mustbe completed at each window spacing. The threshold for the differencebetween scattering distribution shapes measured at two successive windowspacings is determined from the particle size distribution error causedby that threshold difference. In either case, the shape differencebetween distributions F1 and F2 can also be determined by normalizing F1and F2 at the same angle or normalizing them by their sums (as shown inDIFF). Then the mean square (sum of the squares of the differences ateach scattering angle) difference between these normalized functionswill provide the difference in shape between the distributions.

DIFF=SUM(((F1i/SUM(F1i))−(F2i/SUM(F2i)))̂2)

Where SUM=sum over the index i and F1 i and F2 i are either scatteredintensities at the ith scattering angle (scattering distribution) orparticle volumes (or numbers) at the ith particle diameter (particlesize distribution). In the case of dynamic scattering, F1 and F2 couldalso be the power spectrum or autocorrelation function of the scatteredlight detector current. The source beam attenuation due to scatter isalso a direct indicator of multiple scattering. However, the attenuationthreshold is particle size dependent. The first scattering distributionat position A could be inverted to obtain a rough estimate of theparticle size distribution. Then that particle size distribution, thewindow spacing and the beam attenuation at position A could be used tocalculate the new window spacing (position B) which would reduce themultiple scattering to reasonable levels.

In any system, particle counting or ensemble scattering, theconcentration can also be adjusted by adding clean dispersant to theflow loop 10701 in FIG. 107. Then flow loop 10702 could be eliminatedand the computer would only control the injection of clean dispersantinto flow loop 10701. As described before, this clean dispersant wouldbe added under computer control until the count rate or source beamattenuation due to scatter is appropriate to avoid coincidence counts ormultiple scattering. This method may require large amounts of dispersantto reduce the concentration to appropriate levels. This may presentproblems for cost and disposal of expensive or dangerous dispersants.

Also the distribution shape difference method could also be used betweensuccessive particle concentration changes (by sample injection in FIG.107 or dilution) to optimize the particle concentration, withoutadjusting the cell dispersion pathlength (changing between Position A toPosition B).

The design in FIGS. 108 and 109 can be also used to measure dispersionswith high viscosity dispersants (such as pastes) which cannot flowthrough the sample cell. In these cases one of the windows can beremoved from the housing to introduce the sample into the cell, byplacing the sample (smearing the paste onto the window surface) on theopposite window. The window is then replaced and the window spacingadjusted to compress the dispersion between the windows. Again the samewindow spacing adjustment methods, as described above, could be used toobtain the proper number of particles in the beam to avoid multiplescattering for ensemble angular scattering and to avoid coincidences forparticle counting.

In either case, counting or ensemble measurement, the dispersion flowmust be stopped if the window spacing becomes too small to allow flow inthe small gap between the windows. Otherwise, the particles could becounted as they flow through the cell in position B, without theserpentine scan if the particles can flow at sufficient velocity toprovide a high count rate for a fixed detector system. Ensemblescattering measurements could also be made during dispersion flowthrough the cell in Position B. The windows could also extend into thesample cell volume, with regions for passage of particles around bothsides of the windows. Then when the windows are close together, thedispersion flow can continue around the windows, while the flow betweenthe windows is restricted. FIG. 111 shows an extension of this idea,where two optical cones are attached to the windows with opticaladhesive. Only the particles between the tips of the cones, whosespacing is adjusted with the window spacing, will contribute to thescatter signal. The other particles can continue to flow around thecones. And the scattered light from the particles between the cones willnot be rescattered by other particles which are displaced from the pathsof the scattered rays by the cones. FIG. 104 shows a version of FIG. 111with spherical surfaces.

FIG. 112 shows another system which was described previously by thisinventor in the filed Application 1 (FIG. 14 of Application 1). FIG. 112shows an optical system where the light source is spatially filtered bylens 11201 and pinhole 11211. Lens 11202 collimates and projects thesource beam through the particle sample, which is imaged onto the2-dimensional detector arrays by lens 11203. A spatial mask is placed inthe back focal plane of lens 11203 to only pass scattered light over acertain range of scatter angle as defined by the inner and outer radii,R1 and R2, of the annular spatial mask, as shown by mask B. The very lowangle scattering and incident beam are blocked by central stop of theannular aperture in the back focal plane of lens 11203. If the lightbeam passing through the sample cell is not collimated or is focusedinto the cell to increase beam intensity, R1 must be increased to begreater than or equal to the radius of the beam on the mask to block theunscattered light. Application 1 describes many spatial masks which canbe placed in the back focal plane of lens 11203, such as those shown inFIGS. 42, 44, 76, 79, 80, 81, 83, 84, 86, and 88 of Application 1. FIG.112 shows two such annular mask (mask 11221 and mask 11222) systemswhich are accessed through a beamsplitter. The 2-dimensional detectorarrays (such as a CCD array for example) are in the image plane of theparticles. Hence the detector array 11231 sees an image of theparticles, and the sum of the light flux on contiguous pixels associatedwith each particle's image is equal to the scattered light from thatparticle over the angular range defined by the aperture of mask 11221 inthe back focal plane of lens 11203. A beam splitter splits off a portionof the light to a second annular spatial mask (in the back focal planeof lens 11203) and detector array 11232, whose angular range is definedby mask 11222. The angular ranges of the two annular spatial filters arechosen to produce scattered values which are combined by an algorithm todetermine the size of each particle. Radii R1 and R2 can be differentfor mask 11221 and mask 11222. Also either or both masks may be coveredby an absorbing filter with a radial transmission function (see FIG. 88of Application 1 for example), which is different for mask 11221 andmask 11222. These concepts have been described in more detail by thisinventor in this application and previous disclosures and filedapplications. In any case, the sum of signals from contiguous detectorarray pixels, which view the same particle, are analyzed to produce theparticle size of that particle. One such algorithm would be a ratio ofthe corresponding sums (the sum of contiguous pixel signals from theimage of each particle) from the same particle detected by both arrays,detector array 11231 and detector array 11232. The key advantage is thatwhen the particle size is too small to size accurately by dimensionalmeasurements on the image (resolution is limited by pixel size) then thetotal scattered light, through each mask, from each particle may be usedto determine the size, by summing contiguous pixel values for thatparticle. And if the total scattered light is sensitive to particlecomposition, then the ratio of the two scattering signals (each signalfrom different scattering angle ranges, for example) can be used todetermine the particle size more accurately. Said two scattering signalswould consist a first signal which is the sum of contiguous pixels fromdetector array 11231 for a certain particle, and a second signal whichis the sum of contiguous pixels from detector array 11232 for the sameparticle. If the particle image size on a detector array is below thesize of one pixel, the signal may result from only the value measuredfrom the single pixel excited by scattered light from that particle. InFIG. 112, ideally scattered light is only present when a particle ispresent. Each particle image creates an increase in light from a darkbackground level. If the particle is smaller than a single pixel, thenthe amount of scattered light measured by that pixel will indicate thetotal light scattered from that particle in the angular range defined bythe focal plane aperture, providing that particle's size. If more thanone pixel is associated with a particle, those pixel values are summedtogether to obtain the scattered signal from that particle. The increasein pixel signals, relative to the background signal measured withoutparticles, are summed to produce the total light scattered from thatparticle in the angular range of the annular aperture in FIG. 112. Theseideas can be extended to more than two detector arrays or more than twoscattering angles, simply by adding more spatial masks and detectors byusing additional beamsplitters. In this way, each pixel in the detectorarray creates a small independent interaction volume, providingindividual detection of a very small particle contained in thatinteraction volume, with low coincidence probability. But yet contiguouspixels can be combined to measure particles of sizes approaching thedimensions of the entire detector array's image in the sample cell. Thesize dynamic range is enormous. FIG. 112 could also be used with asource beam which is focused into the sample cell to reduce theinteraction volume and increase the beam intensity and scattered signal.In this case the center portion of the mask must be increased in size toblock the diverging light from the source so that each detector arrayonly sees scattered light. The optical source used FIG. 112 could be apulsed broad band source such as a xenon flash lamp which producesbroadband light to wash out the Mie resonances, and which produces ashort light pulse to freeze the motion of particles flowing through thecell. However, this technique can also be used with the methodsdescribed for FIGS. 107 through 111, without the need for serpentinescanning. Repeated cycles of Position A, to exchange dispersion, andPosition B, with stopped flow, would be used. During the stopped flow inPosition B, the optical system in FIG. 112 would collect an image oneach array, without the need for a pulsed source. This process may bemuch slower than the continuous flow case due to the time required tostop flow and change to position B. The change to Position B is onlyneeded when the coincidence count level is significant due to pixelswhich see scattered light from more than one particle during eachmeasurement. Then the reduced dispersion pathlength in Position B wouldreduce the level of coincidence counts.

This inventor has also disclosed and filed applications which describemethods and apparatus which can determine the shape of particles bymeasuring scattered light in various scattering planes, as described inFIGS. 79, 80, 81, 83, 84, 86, and 88 of Application 1, for example. MaskA in FIG. 112 shows an aperture which measures scatter from only a smallrange of scattering planes. A scattering plane is the plane whichcontains the incident light beam and the scattered ray. Mask A can beplaced in the positions of mask 11221 and/or mask 11222. As mask Arotates, the mask aperture will capture light from different scatteringplanes, sequentially. The total light from contiguous pixels of eachparticle image will represent the scattered light for the angular rangeand range of scattering planes defined by the inner and outer radii ofthe aperture and the rotation position of that aperture during the timewhen the detector array pixel currents are integrated. If the detectorarray pixel currents are integrated and sampled at various rotationpositions of Mask A, the scattering values, for each pixel in eachdetector array, will be sampled for various scattering planessequentially. The total integrated currents from the contiguous pixelsrepresenting the image of each single particle are measured and summedwhen both mask 11221 and mask 11222 are seeing the same angular positionof the scattering plane. The digitized detector array images provide thesame information for each particle in the detector array images as thebinary optic arrays and masks (see FIGS. 79, 80, 81, 82, 83, 84, 85, 86,87, and 88 in Application 1, for example), described previously by thisinventor, provided for a single particle in a single interaction volume.Therefore, all of the analysis techniques, described previously by thisinventor, can be used to determine particle size and shape for eachparticle in these detector array images, by using the total signal fromeach particle in each image. Essentially, the system in FIG. 112measures the scattered light from many interaction volumes in paralleland measures the scattered light from each scattering plane sequentiallyfor all interaction volumes, as the mask rotates to each position. Thesystems in Application 1 (FIG. 78 for example) measure all of thescattering planes in parallel and measures each particle sequentially asit passes through a single interaction volume. Each range of scatteringangle or radial (angular) weighting function is measured by a separatemask and detector array system, in FIG. 112. All such systems view thesame particles through beamsplitters and each of such systems measureseach scattering plane sequentially as the mask for that system rotates.Two or more masks can have different weighting functions (Wij inApplication 1) and/or different range of scattering angles. Additionalmask/detector systems can be added by placing additional beamsplittersin the optical paths after Lens 11203. So that the contiguous pixel sumfor each particle can be measured for all of the scattering angles,weighting functions, and scattering planes required to determine thesize and/or shape of each particle using the methods described inApplication 1 (see pages 101 to 109 in Application 1 for example).

FIG. 65 shows another version of FIG. 112, where the functions of Mask Aand Mask B are separated into Mask A1 (like the rotating Mask A of FIG.112), and Mask B1 and Mask B2 (both like the Mask B of FIG. 112). MaskA1 selects different scattering planes as it rotates; and the lightpassing through Mask A1 is split by the beam splitter to two stationarymasks, Mask B1 and Mask B2 which have different weighting functions (Wijin Application 1) and/or different range of scattering angles (asdefined by R1 and R2 in FIG. 112 for example). All masks are in planeswhich are conjugate to the back focal plane of Lens 6504 and alldetector arrays are in planes which are conjugate to the particles. Allof the features of FIG. 112 apply to FIG. 65, including the use of aconverging source beam instead of a collimated beam. However, FIG. 65has the advantage of only needing one rotating mask for all of thedetector arrays. Again, by using more beam splitters, more type B masksand accompanying detector arrays may be added to extend the size rangeof the instrument by measuring at other weighting functions (Wij inApplication 1) and/or other ranges of scattering angles (as defined byR1 and R2 in FIG. 112 for example).

This rotating mask method can also be used in any system which measuresa single interaction volume (FIG. 78 in Application 1 for example). Therotating mask, lens, and a single detector would replace the detectorarray in FIG. 78. The lens would collect light which passes through themask and focus that light onto the single detector. The mask must rotatevery quickly to capture all of the scattering plane measurements on asingle detector sequentially, as each particle passes through theinteraction volume. Also this system can be used with the methodsdescribed above in FIGS. 107, 108, 109 and 111 to scan a sample betweentwo windows or on a microscope slide. The scan could stop at eachposition on the sample to allow full rotation of the mask on a singleparticle, without particle motion. By using beamsplitters and multiplemask/lens/detector systems, the scatter signals for each particle can bemeasured for all of the scattering angles, weighting functions, andscattering planes required to determine the size and/or shape of eachparticle using the methods described in Application 1 (see pages 101 to109 in Application 1 for example).

Also notice that most counting systems, including these counting systemsand other systems described in Application 1, can be combined with anensemble scattering system by using a beam splitter to split off aportion of the scattered light from the ensemble system to the countingsystem (or visa versa).

In some cases, where scattered light at very high scattering angles mustbe measured to determine the size of very small particles, the samplecell can be modified as shown in FIG. 40 to reduce Fresnel reflectionsat the air/glass interfaces (also described in FIG. 21 of Application1). The particle dispersion fills the volume between the two sample cellwindows. Prism 4001 is attached to the entrance of the sample cell andPrism 4002 is attached to the exit of the sample cell, using refractiveindex matching adhesive. Prism 4001 and Prism 4002 could also directlyreplace the windows by using appropriate seals to interface the prismsto an enclosed cavity though which the dispersion flows. The scatteredlight in lowest scatter angle range is captured by Lens 4005, whichfocuses the light onto a detector array. This array could be placed inthe back focal plane of Lens 4005. The light from the light source iscollected by a central element of the detector array to monitor scatterattenuation of the light beam. Alternatively, that focused source lightcan pass through a hole in the detector array. Lens 4011, Lens 4012,Lens 4013, and Lens 4014 collect scattered light from higher ranges ofscattering angle. The detectors are not shown for these lenses, but theycan consist of single or multiple detectors, or detector arrays, placedin the back focal plane of each lens. Each detector or detector element,measures scattered light from a different range of scattering angles.The air/glass prism surfaces are at much lower incidence angles forscattered light rays than would be the case for the simple plano glasswindows. Hence the Fresnel reflection losses are much lower. The prismsurfaces can also be anti-reflection coated to further reduce thesereflections. The interaction volume in FIG. 40 can be the interactionvolume of any scattering system including a dynamic scattering system orstatic angular scattering system.

1. Apparatus for optimizing path length of a light beam through aparticle dispersion to improve accuracy of measurement of lightscattered from particles, comprising: a) an optical system forilluminating a particle dispersion, b) a detection system comprising atleast one detector for quantifying light scattered by at least one ofsaid particles, c) a sample cell, comprising two optical windows, whichconfine said particle dispersion and pass light, from a light source,through said particle dispersion to produce light scattered by saidparticle dispersion, and d) means for adjusting a separation betweensaid optical windows to change a path length of light, from said lightsource, through said sample cell.
 2. The apparatus of claim 1, whereinsaid path length is optimized to reduce multiple scattering in anensemble scattering measurement.
 3. The apparatus of claim 1, whereinsaid path length is optimized to reduce coincidence counts in a particlecounting measurement.
 4. The apparatus of claim 1, wherein said pathlength is optimized to hold particles in a thin layer of dispersant forparticle counting measurements using said optical system and detectionsystem, wherein the particles are scanned over said thin layer tomeasure scattered light from various locations on said thin layer. 5.The apparatus of claim 4, wherein the particle dispersion has a particleconcentration which is adjusted to provide a specified number ofparticles per unit area in said thin layer.
 6. The apparatus of claim 1,wherein the sample cell defines first and second sides, wherein theoptical system and detection system are positioned in a vicinity of saidfirst side, and wherein there is a retroreflector positioned in avicinity of said second side, wherein the retroreflector comprises meansfor removing angular drift of a light beam caused by drift in position,or drift in optical properties, of said optical system, said samplecell, and/or said detection system.
 7. The apparatus of claim 6, whereinthe adjusting means comprises means for setting the path length to afixed value.
 8. A method for determining an optimum path length of alight beam passing through a particle dispersion, so as to reduceinaccuracies in particle analysis caused by multiple scattering of lightfrom particles, the method comprising the steps of: a) determining aspecified value of a path length which produces excessive multiplescattering, b) adjusting said path length to a specified value, c)measuring first scattered light values at said specified value of pathlength, d) reducing said path length to a second value, e) measuringsecond scattered light values at said second value of said path length,f) determining a difference between said second scattered light valuesand said first scattered light values, g) if said difference is greaterthan a specified limit, repeating steps (b) through (f), while settingsaid specified value of path length, in step (b), to said second valueof said path length, h) if said difference is less than a specifiedlimit, using said second scattered light values to determine particlecharacteristics.
 9. The method of claim 8, further comprising selectingsaid difference between said second scattered light values and firstscattered light values to be a difference in functional shape of thescattered light as a function of scattering angle.
 10. The method ofclaim 8, further comprising the step of removing angular drift of alight beam caused by drift in position, or drift in optical properties,of an optical system and/or a detection system.
 11. A method fordetermining an optimum path length of a light beam passing through aparticle dispersion, so as to reduce inaccuracies in particle analysiscaused by scattering measurement errors, the method comprising the stepsof: a) adjusting a path length to a specified value, b) measuringscattered light values at said specified value of said path length, c)calculating an optimum value of path length based upon said specifiedvalue of said path length and said scattered light values, d) adjustingsaid path length to said optimum value of path length, e) measuringscattered light values at said optimum value of path length and usingscattered light values to determine particle characteristics.
 12. Themethod of claim 11, further comprising selecting said scattered lightvalues to be based on optical attenuation due to light scattering. 13.Apparatus for measuring scattered light from individual particles whichare nearly confined to a plane on a surface or in a thin layer of adispersant, comprising: a) an optical system for illuminating saidparticles, b) a detection system comprising at least one detector forquantifying light scattered from a specific region on said plane, and c)mechanical means for moving an interaction volume of said optical systemand detection system to various locations on said plane to measureseparately light scattered at each location.
 14. Apparatus for removingangular drift in a system for analyzing particles, comprising: a) anoptical system for illuminating a particle dispersion, b) a detectionsystem comprising at least one detector for quantifying light scatteredby at least one particle, and c) a sample cell, comprising two opticalwindows, wherein the windows confine the particle dispersion and passlight, from a light source, through said particle dispersion to producelight scattered by said particle dispersion, wherein said optical systemand detection system are attached to a first side of said sample cell,and wherein the apparatus includes a retroreflector positioned in avicinity of a second side of said sample cell, wherein theretroreflector comprises means for removing angular drift of a lightbeam caused by drift in position, or drift in optical properties, ofsaid optical system, said sample cell, and/or said detection system.